Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion...Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.展开更多
The main cable is the primary load-bearing component of a suspension bridge,continuously exposed to harsh environmental conditions,such as wind and rain,throughout the year.These adverse conditions contribute to varyi...The main cable is the primary load-bearing component of a suspension bridge,continuously exposed to harsh environmental conditions,such as wind and rain,throughout the year.These adverse conditions contribute to varying degrees of degradation and damage to the main cable,necessitating regular inspections to prevent catastrophic failures.Traditional manual inspection methods not only suffer from low efficiency but also pose significant safety risks to personnel.To address these challenges and ensure the safe and effective inspection of suspension bridge main cables,this study introduces a novel cooperative climbing robot,designated as Main Cable Robot Version II(CCRobot-M-II),inspired by the locomotion of the inchworm.The robot employs an alternating opening and closing mechanism of four gripper sets,mimicking the inchworm's movement to achieve efficient crawling along the suspension bridge handrails.This paper provides a comprehensive analysis of the structural design,key components,and motion mechanisms of CCRobot-M-II.A detailed force analysis of the robot's crawling process is also presented,followed by the design of the control system and the development of an efficient motion control algorithm.Laboratory experiments demonstrate that the robot achieves a positional error of 00.64%during crawling,with a maximum average crawling speed of 7.6 m/min.Furthermore,the biomimetic design enables the robot to overcome obstacles up to 30 mm in height and possess the capability to handle suspension bridge cables with spans ranging from 740 to 1100 mm.Finally,CCRobot-M-II successfully conducted an inspection of the main cable on a suspension bridge,marking the world's first successful deployment of a climbing robot for main cable inspection on a suspension bridge.展开更多
Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance,adaptability,and safe interactions within unstructured environments.Over the past decade(2015-2025),significant advance...Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance,adaptability,and safe interactions within unstructured environments.Over the past decade(2015-2025),significant advancements have trans-formed their capabilities through novel designs inspired by biological systems,advanced modeling frameworks,sophisti-cated control strategies,and integration into diverse real-world applications.Recent innovations in multifunctional mate-rials and emerging actuation technologies have markedly expanded manipulator performance,reliability,and dexterity.Concurrently,developments in modeling have progressed from simplified geometric methods toward highly accurate physics-based and hybrid data-driven approaches,substantially improving real-time prediction and controllability.Coupled with these developments,adaptive and robust control strategies-including learning-based techniques-have enabled unprec-edented autonomy and precision in challenging application domains such as Minimally Invasive Surgery(MIS),precision agriculture,deep-sea exploration,disaster recovery,and space missions.Despite these remarkable strides,key challenges remain,notably regarding scalability,long-term material durability,robust integrated sensing,and standardized evaluation procedures.This review comprehensively synthesizes recent advances,critically evaluates state-of-the-art methodologies,and systematically identifies existing gaps to provide a clear roadmap and targeted research directions,guiding future developments toward the broader adoption and optimal utilization of soft robotic manipulators.展开更多
Trajectory tracking for nonlinear robotic systems remains a fundamental yet challenging problem in control engineering,particularly when both precision and efficiency must be ensured.Conventional control methods are o...Trajectory tracking for nonlinear robotic systems remains a fundamental yet challenging problem in control engineering,particularly when both precision and efficiency must be ensured.Conventional control methods are often effective for stabilization but may not directly optimize long-term performance.To address this limitation,this study develops an integrated framework that combines optimal control principles with reinforcement learning for a single-link robotic manipulator.The proposed scheme adopts an actor–critic structure,where the critic network approximates the value function associated with the Hamilton–Jacobi–Bellman equation,and the actor network generates near-optimal control signals in real time.This dual adaptation enables the controller to refine its policy online without explicit system knowledge.Stability of the closed-loop system is analyzed through Lyapunov theory,ensuring boundedness of the tracking error.Numerical simulations on the single-link manipulator demonstrate that themethod achieves accurate trajectory followingwhile maintaining lowcontrol effort.The results further showthat the actor–critic learning mechanism accelerates convergence of the control policy compared with conventional optimization-based strategies.This work highlights the potential of reinforcement learning integrated with optimal control for robotic manipulators and provides a foundation for future extensions to more complex multi-degree-of-freedom systems.The proposed controller is further validated in a physics-based virtual Gazebo environment,demonstrating stable adaptation and real-time feasibility.展开更多
Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This stu...Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This study presents a cognitive control strategy that integrates a Numerical Feedforward Inverse Dynamic Controller(NFIDC)with a Feedback Radial Basis Function Neural Network(FRBFNN).The robot’s mechanical structure was designed in SolidWorks 2022 SP2.0 and validated under operational loads using finite element analysis in ANSYS 2022 R1.The NFIDC-FRBFNN framework merges proactive inverse dynamic compensation with adaptive neural learning to achieve smooth torque responses and accurate motion control.A two-stage simulation evaluation was conducted.In the first stage,the controller was tested in a simulated hospital environment under both ideal and non-ideal conditions.In the second,it was benchmarked against four established controllers-Neural Network Model Reference Adaptive(NNMRA),Z-number Fuzzy Logic(Z-FL),Adaptive Dynamic Controller(ADC),and Fuzzy Logic-PID(FL-PID)—using circular and lemniscate trajectories.Across ten runs,the proposed controller achieved the lowest tracking errors under all conditions.Under ideal conditions,it achieved average improvements of 55.24%,75.75%,and 55.20%in integral absolute error(IAE),integral squared error(ISE),and mean absolute error(MAE),respectively,with coefficient of variation(CV)reductions above 55%.Under non-ideal conditions,average improvements exceeded 64%in IAE,77%in ISE,and 66%in MAE,while maintaining CV reductions above 57%.These results confirm that the NFIDC-FRBFNN controller offers superior accuracy,robustness,and consistency for real-time path tracking in healthcare robotics.展开更多
A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of contro...A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of controlling the po- sition and attitude of both the satellite base and the payload grasped by the manipulator end effectors. The equations of motion in reduced-order form for the constrained system are derived by incorporating the constraint equations in terms of accelerations into Kane＇s equations of the unconstrained system. Model analysis shows that the resulting equations perfectly meet the requirement of adaptive controller design. Consequently, by using an indirect approach, an adaptive control scheme is proposed to accomplish position/attitude trajectory tracking control with the uncertain parameters be- ing estimated on-line. The actuator redundancy due to the closed-loop constraints is utilized to minimize a weighted norm of the joint torques. Global asymptotic stability is proven by using Lyapunov＇s method, and simulation results are also presented to demonstrate the effectiveness of the proposed approach.展开更多
This paper presents a study on bioinspired closed-loop Central Pattern Generator(CPG)based control of a robot fish for obstacle avoidance and direction tracking.The biomimetic robot fish is made of a rigid head with a...This paper presents a study on bioinspired closed-loop Central Pattern Generator(CPG)based control of a robot fish for obstacle avoidance and direction tracking.The biomimetic robot fish is made of a rigid head with a pair of pectoral fins,a wire-driven active body covered with soft skin,and a compliant tail.The CPG model consists of four input parameters:the flapping amplitude,the flapping angular velocity,the flapping offset,and the time ratio between the beat phase and the restore phase in flapping.The robot fish is equipped with three infrared sensors mounted on the left,front and right of the robot fish,as well as an inertial measurement unit,from which the surrounding obstacles and moving direction can be sensed.Based on these sensor signals,the closed-loop CPG-based control can drive the robot fish to avoid obstacles and to track designated directions.Four sets of experiments are presented,including avoiding a static obstacle,avoiding a moving obstacle,tracking a designated direction and tracking a designated direction with an obstacle in the path.The experiment results indicated that the presented control strategy worked well and the robot fish can accomplish the obstacle avoidance and direction tracking effectively.展开更多
Serving the Stewart mechanism as a wheel-legged structure,the most outstanding superiority of the proposed wheel-legged hybrid robot(WLHR)is the active vibration isolation function during rolling on rugged terrain.How...Serving the Stewart mechanism as a wheel-legged structure,the most outstanding superiority of the proposed wheel-legged hybrid robot(WLHR)is the active vibration isolation function during rolling on rugged terrain.However,it is difficult to obtain its precise dynamic model,because of the nonlinearity and uncertainty of the heavy robot.This paper presents a dynamic control framework with a decentralized structure for single wheel-leg,position tracking based on model predictive control(MPC)and adaptive impedance module from inside to outside.Through the Newton-Euler dynamic model of the Stewart mechanism,the controller first creates a predictive model by combining Newton-Raphson iteration of forward kinematic and inverse kinematic calculation of Stewart.The actuating force naturally enables each strut to stretch and retract,thereby realizing six degrees-of-freedom(6-DOFs)position-tracking for Stewart wheel-leg.The adaptive impedance control in the outermost loop adjusts environmental impedance parameters by current position and force feedback of wheel-leg along Z-axis.This adjustment allows the robot to adequately control the desired support force tracking,isolating the robot body from vibration that is generated from unknown terrain.The availability of the proposed control methodology on a physical prototype is demonstrated by tracking a Bezier curve and active vibration isolation while the robot is rolling on decelerate strips.By comparing the proportional and integral(PI)and constant impedance controllers,better performance of the proposed algorithm was operated and evaluated through displacement and force sensors internally-installed in each cylinder,as well as an inertial measurement unit(IMU)mounted on the robot body.The proposed algorithm structure significantly enhances the control accuracy and vibration isolation capacity of parallel wheel-legged robot.展开更多
1Introduction To date,in model-based gait-planning methods,the dynamics of the center of mass(COM)of bipedal robots have been analyzed by establishing their linear inverted pendulum model(LIPM)or extended forms(Owaki ...1Introduction To date,in model-based gait-planning methods,the dynamics of the center of mass(COM)of bipedal robots have been analyzed by establishing their linear inverted pendulum model(LIPM)or extended forms(Owaki et al.,2010;Englsberger et al.,2015;Xie et al.,2020).With regard to model-based gait-generation methods for uphill and downhill terrain,Kuo(2007)simulated human gait using an inverted pendulum,which provided a circular trajectory for the COM rather than a horizontal trajectory.He found that a horizontal COM trajectory consumed more muscle energy.Massah et al.(2012)utilized a 3D LIPM and the concept of zero moment point(ZMP).They developed a trajectory planner using the semi-elliptical motion equations of an NAO humanoid robot and simulated walking on various sloped terrains using the Webots platform.展开更多
The semi-round rigid feet would cause position-posture deviation problem because the actual foothold position is hardly known due to the rolling effect of the semi-round rigid feet during the robot walking. The positi...The semi-round rigid feet would cause position-posture deviation problem because the actual foothold position is hardly known due to the rolling effect of the semi-round rigid feet during the robot walking. The position-posture deviation problem may harm to the stability and the harmony of the robot, or even makes the robot tip over and fail to walk forward. Focused on the position-posture deviation problem of multi-legged walking robots with semi-round rigid feet, a new method of position-posture closed-loop control is proposed to solve the position-posture deviation problem caused by semi-round rigid feet, based on the inverse velocity kinematics of the multi-legged walking robots. The position-posture closed-loop control is divided into two parts: the position closed-loop control and the posture closed-loop control. Thus, the position-posture control for the robot which is a tight coupling and nonlinear system is decoupled. Co-simulations of position-posture open-loop control and position-posture closed-loop control by MATLAB and ADAMS are implemented, respectively. The co-simulation results verify that the position-posture closed-loop control performs well in solving the position-posture deviation problem caused by semi-round rigid feet.展开更多
Dear Editor,This letter considers the formation control of multiple mobile robot systems(MMRS)that only relies on the local observation information.A new distributed finite-time observer is proposed for MMRS under dir...Dear Editor,This letter considers the formation control of multiple mobile robot systems(MMRS)that only relies on the local observation information.A new distributed finite-time observer is proposed for MMRS under directed graph to estimate the relative information between each follower robot and the leader robot.Then the formation control problem is transformed into the tracking problem and a finite-time tracking controller is proposed based on the robot model feature.展开更多
Rollover accidents involving agricultural wheeled robots,accompanied by severe mechanical impacts,pose serious threats to operational safety and reduce functional efficiency.To address this issue,an active rollover pr...Rollover accidents involving agricultural wheeled robots,accompanied by severe mechanical impacts,pose serious threats to operational safety and reduce functional efficiency.To address this issue,an active rollover prevention strategy is proposed,utilizing a single‐gimbal control moment gyro(SGCMG),to stabilize typical agricultural robots and prevent potential rollovers.To match the free oscillation of the pivot front axle,a novel recovery torque model of the coupled robot‐SGCMG system is established,in which two patterns are introduced to refine the rollover process with uncertain parameters.Additionally,a lateral stability index is adopted and analyzed to assess the hazard level of potential rollovers.Aimed at handling uncertain parameters and hazard levels,an adaptive backstepping control strategy is developed for real‐time anti‐rollover implementation.Within this strategy,control gains are adaptively tuned based on theoretical derivations,thereby suppressing rollover tendency while minimizing tuning effort.For verification,a scaled experimental platform,designed according to similarity theory,is constructed to ensure safety of personnel and equipment.Experimental results show that the proposed method can precisely regulate the output torque of the gyro,rapidly and effectively mitigating the risk of imminent rollover.This method provides a promising solution for wheeled robot stability and a theoretical basis for advanced safety control in agricultural robotics.展开更多
Inspired by bacterial motility mechanisms,Magnetic Helical Miniature Robots(MHMRs)exhibit promising applications in biomedical fields due to their efficient locomotion and compatibility with biological tissues.In this...Inspired by bacterial motility mechanisms,Magnetic Helical Miniature Robots(MHMRs)exhibit promising applications in biomedical fields due to their efficient locomotion and compatibility with biological tissues.In this review,we systematically survey the basics of MHMRs,from propulsion mechanism,magnetization and control methods to biomedical applications,aiming to provide readers with an easily understandable overview and fundamental knowledge on implementing MHMRs.The MHMRs are actuated by rotating magnetic fields,achieving steering and rotation through magnetic torque,and converting rotation into forward motion through the helical structure.Magnetization methods for MHMRs are reviewed into three types:attaching magnets,magnetic coatings,and magnetic powder doping.Additionally,this review discusses the control methods for MHMRs,covering imaging techniques,path tracking control—including classical control algorithms and increasingly popular learning-based methods,and swarm control.Subsequently,a comprehensive survey is conducted on the biomedical applications of MHMRs in the treatment of vascular diseases,drug delivery,cell delivery,and their integration with catheters.We finally provide a perspective about future challenges in MHMR research,including enhancing functional design capabilities,developing swarm-assisted independent control mechanisms,refining in vivo imaging techniques,and ensuring robust biocompatibility for safe medical use.展开更多
The wheeled bipedal robots have great application potential in environments with a mixture of structured and unstructured terrain. However, wheeled bipedal robots have problems such as poor balance ability and low mov...The wheeled bipedal robots have great application potential in environments with a mixture of structured and unstructured terrain. However, wheeled bipedal robots have problems such as poor balance ability and low movement level on rough roads. In this paper, a novel and low-cost wheeled bipedal robot with an asymmetrical five-link mechanism is proposed, and the kinematics of the legs and the dynamics of the Wheeled Inverted Pendulum (WIP) are modeled. The primary balance controller of the wheeled bipedal robot is built based on the Linear Quadratic Regulator (LQR) and the compensation method of the virtual pitch angle adjusting the Center of Mass (CoM) position, then the whole-body hybrid torque-position control is established by combining attitude and leg controllers. The stability of the robot’s attitude control and motion is verified with simulations and prototype experiments, which confirm the robot’s ability to pass through complex terrain and resist external interference. The feasibility and reliability of the proposed control model are verified.展开更多
This paper proposes a separated trajectory tracking controller for fishing ships at sea state level 6 to solve the trajectory tracking problem of a fishing ship in a 6-level sea state,and to adapt to different working...This paper proposes a separated trajectory tracking controller for fishing ships at sea state level 6 to solve the trajectory tracking problem of a fishing ship in a 6-level sea state,and to adapt to different working environments and safety requirements.The nonlinear feedback method is used to improve the closed-loop gain shaping algorithm.By introducing the sine function,the problem of excessive control energy of the system can be effectively solved.Moreover,an integral separation design is used to solve the influence of the integral term in conventional PID controllers on the transient performance of the system.In this paper,a common 32.98 m large fiberglass reinforced plastic(FRP)trawler is adopted for simulation research at the winds scale of Beaufort No.7.The results show that the track error is smaller than 3.5 m.The method is safe,feasible,concise and effective and has popularization value in the direction of fishing ship trajectory tracking control.This method can be used to improve the level of informatization and intelligence of fishing ships.展开更多
Rotary steering systems(RSSs)have been increasingly used to develop horizontal wells.A static push-the-bit RSS uses three hydraulic modules with varying degrees of expansion and contraction to achieve changes in the p...Rotary steering systems(RSSs)have been increasingly used to develop horizontal wells.A static push-the-bit RSS uses three hydraulic modules with varying degrees of expansion and contraction to achieve changes in the pushing force acting on the wellbore in different sizes and directions within a circular range,ultimately allowing the wellbore trajectory to be drilled in a predetermined direction.By analyzing its mathematical principles and the actual characteristics of the instrument,a vector force closed-loop control method,including steering and holding modes,was designed.The adjustment criteria for the three hydraulic modules are determined to achieve rapid adjustment of the vector force.The theoretical feasibility of the developed method was verified by comparing its results with the on-site application data of an imported rotary guidance system.展开更多
As robotic surgery provides clinical benefits and increases on a global scale,it also signifies the transition from direct manual control of surgical instruments to digital connectivity and teleoperation.The digital c...As robotic surgery provides clinical benefits and increases on a global scale,it also signifies the transition from direct manual control of surgical instruments to digital connectivity and teleoperation.The digital coupling between human control inputs and surgical motion replaces the previous physical link.Robotic surgery is therefore in effect‘surgery-by-wire’,the term capturing the engineering phenomenon that has also occurred in the‘fly-by-wire’of aviation and‘drive-by-wire’of cars.This paper reviews the fundamental commonality across domains.Intrinsic to‘by-wire’control is digital processing,which generates the control signal to the effector.This processing enables a progressive spectrum of motion modulation,from precision and stability of motion,through assistance and envelope protection,to automation.Precision now manifests in all three domains.In modern aircraft and cars,higher-order assistance is commonplace,such as flight envelope protection,with analogous support in driving,as well as significant automation.In robotic surgery,such assistance and automation have not yet entered wider clinical practice,with concepts such as envelope protection requiring further definition.The digital interface combined with telecommunication has also enabled teleoperation in all domains.Therefore,motion‘by-wire’has enhanced performance across industries.A cross-domain perspective will be increasingly useful to facilitate technology transfer and catalyse progress in robotic surgery.As the pan-industry digital transformation evolves,important principles can be derived for application in robotic surgery.展开更多
The problem of disturbance rejection in humanoid robots has been properly studied,with most prior work focusing on hip-ankle-stepping compliance control strategies or whole-body inverse dynamics control.This paper pre...The problem of disturbance rejection in humanoid robots has been properly studied,with most prior work focusing on hip-ankle-stepping compliance control strategies or whole-body inverse dynamics control.This paper presents an adaptive disturbance rejection balance controller based on a Variable-inertia Centroidal Model Predictive Control(ViC-MPC)approach,designed to address both minor disturbances that affect standing balance and major disturbances requiring stepping adjustments.The controller also facilitates reliable balance recovery after stepping adjustments.The humanoid robot is modeled as a spatial variable-inertia ellipsoid,representing the distribution of centroidal dynamics,with the contact wrenches optimized in real-time through a customized MPC formulation.Inspired by capturability-based constraints,we propose an adaptive dynamic stability transition strategy.This strategy is activated based on the Retrospective Horizon Average Centroidal Velocity(RHACV)and the Capture Point(CP),ensuring effective stepping adjustments and disturbance rejection.With the torque-controlled humanoid robot BHR8P,extensive simulation and experimental results demonstrate the effectiveness of the proposed method,highlighting its capability to adapt to and recover from various disturbances with improved stability.展开更多
Energy efficiency stands as an essential factor when implementing deep reinforcement learning(DRL)policies for robotic control systems.Standard algorithms,including Deep Deterministic Policy Gradient(DDPG),primarily o...Energy efficiency stands as an essential factor when implementing deep reinforcement learning(DRL)policies for robotic control systems.Standard algorithms,including Deep Deterministic Policy Gradient(DDPG),primarily optimize task rewards but at the cost of excessively high energy consumption,making them impractical for real-world robotic systems.To address this limitation,we propose Physics-Informed DDPG(PI-DDPG),which integrates physics-based energy penalties to develop energy-efficient yet high-performing control policies.The proposed method introduces adaptive physics-informed constraints through a dynamic weighting factor(λ),enabling policies that balance reward maximization with energy savings.Our motivation is to overcome the impracticality of rewardonly optimization by designing controllers that achieve competitive performance while substantially reducing energy consumption.PI-DDPG was evaluated in nine MuJoCo continuous control environments,where it demonstrated significant improvements in energy efficiency without compromising stability or performance.Experimental results confirm that PI-DDPG substantially reduces energy consumption compared to standard DDPG,while maintaining competitive task performance.For instance,energy costs decreased from 5542.98 to 3119.02 in HalfCheetah-v4 and from1909.13 to 1586.75 in Ant-v4,with stable performance in Hopper-v4(205.95 vs.130.82)and InvertedPendulum-v4(322.97 vs.311.29).Although DDPG sometimes yields higher rewards,such as in HalfCheetah-v4(5695.37 vs.4894.59),it requires significantly greater energy expenditure.These results highlight PI-DDPG as a promising energy-conscious alternative for robotic control.展开更多
Autonomous legged robots,capable of navigating uneven terrain,can perform a diverse array of tasks.However,designing locomotion controllers remains challenging.In particular,designing a controller based on durable and...Autonomous legged robots,capable of navigating uneven terrain,can perform a diverse array of tasks.However,designing locomotion controllers remains challenging.In particular,designing a controller based on durable and reliable proprioceptive sensors,is essential for achieving adaptability.Presently,the controller must either be manually designed for specific robots and tasks,or developed using machine-learning techniques,which require extensive training time and result in complex controllers.Inspired by animal locomotion,we propose a simple yet comprehensive closed-loop modular framework that utilizes minimal proprioceptive feedback(i.e.,the Coxa-Femur(CF)joint angle),enabling a quadruped robot to efficiently navigate unpredictable and uneven terrains,including the step and slope.The framework comprises a basic neural control network capable of rapidly learning optimized motor patterns,and a straightforward module for sensory feedback sharing and integration.In a series of experiments,we show that integrating sensory feedback into the base neural control network aids the robot in continually learning robust motor patterns on flat,step,and slope terrain,compared with the open-loop base framework.Sharing sensory feedback information across the four legs enables a quadruped robot to proactively navigate unpredictable steps with minimal interaction.Furthermore,the controller remains functional even in the absence of sensor signals.This control configuration was successfully transferred to a physical robot without any modifications.展开更多
文摘Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.
基金Shenzhen Science and Technology Program(Grant No.20220817171811004)(Grant No.RCBS20231211090816033)+4 种基金the Major Key Project of PCL,China under Grant PCL2025A13Longgang District,Shenzhen's"Ten-Action Plan"for Supporting Innovation Projects(Grant No.LGKCSDPT2024002,LGKCSDPT2024003,LGKCSDPT2024004)the"Zhiguo"Action of Guangxi Science and Technology Program(Grant No.ZG2503980003)Guangdong S&T Program under(Grant No.2025B0909040003)Guangdong Provincial Leading Talent Program(Grant No.2024TX08Z319).
文摘The main cable is the primary load-bearing component of a suspension bridge,continuously exposed to harsh environmental conditions,such as wind and rain,throughout the year.These adverse conditions contribute to varying degrees of degradation and damage to the main cable,necessitating regular inspections to prevent catastrophic failures.Traditional manual inspection methods not only suffer from low efficiency but also pose significant safety risks to personnel.To address these challenges and ensure the safe and effective inspection of suspension bridge main cables,this study introduces a novel cooperative climbing robot,designated as Main Cable Robot Version II(CCRobot-M-II),inspired by the locomotion of the inchworm.The robot employs an alternating opening and closing mechanism of four gripper sets,mimicking the inchworm's movement to achieve efficient crawling along the suspension bridge handrails.This paper provides a comprehensive analysis of the structural design,key components,and motion mechanisms of CCRobot-M-II.A detailed force analysis of the robot's crawling process is also presented,followed by the design of the control system and the development of an efficient motion control algorithm.Laboratory experiments demonstrate that the robot achieves a positional error of 00.64%during crawling,with a maximum average crawling speed of 7.6 m/min.Furthermore,the biomimetic design enables the robot to overcome obstacles up to 30 mm in height and possess the capability to handle suspension bridge cables with spans ranging from 740 to 1100 mm.Finally,CCRobot-M-II successfully conducted an inspection of the main cable on a suspension bridge,marking the world's first successful deployment of a climbing robot for main cable inspection on a suspension bridge.
基金Open access funding provided by The Science,Technology&Innovation Funding Authority(STDF)in cooperation with The Egyptian Knowledge Bank(EKB).
文摘Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance,adaptability,and safe interactions within unstructured environments.Over the past decade(2015-2025),significant advancements have trans-formed their capabilities through novel designs inspired by biological systems,advanced modeling frameworks,sophisti-cated control strategies,and integration into diverse real-world applications.Recent innovations in multifunctional mate-rials and emerging actuation technologies have markedly expanded manipulator performance,reliability,and dexterity.Concurrently,developments in modeling have progressed from simplified geometric methods toward highly accurate physics-based and hybrid data-driven approaches,substantially improving real-time prediction and controllability.Coupled with these developments,adaptive and robust control strategies-including learning-based techniques-have enabled unprec-edented autonomy and precision in challenging application domains such as Minimally Invasive Surgery(MIS),precision agriculture,deep-sea exploration,disaster recovery,and space missions.Despite these remarkable strides,key challenges remain,notably regarding scalability,long-term material durability,robust integrated sensing,and standardized evaluation procedures.This review comprehensively synthesizes recent advances,critically evaluates state-of-the-art methodologies,and systematically identifies existing gaps to provide a clear roadmap and targeted research directions,guiding future developments toward the broader adoption and optimal utilization of soft robotic manipulators.
基金supported in part by the National Science and Technology Council under Grant NSTC 114-2221-E-027-104.
文摘Trajectory tracking for nonlinear robotic systems remains a fundamental yet challenging problem in control engineering,particularly when both precision and efficiency must be ensured.Conventional control methods are often effective for stabilization but may not directly optimize long-term performance.To address this limitation,this study develops an integrated framework that combines optimal control principles with reinforcement learning for a single-link robotic manipulator.The proposed scheme adopts an actor–critic structure,where the critic network approximates the value function associated with the Hamilton–Jacobi–Bellman equation,and the actor network generates near-optimal control signals in real time.This dual adaptation enables the controller to refine its policy online without explicit system knowledge.Stability of the closed-loop system is analyzed through Lyapunov theory,ensuring boundedness of the tracking error.Numerical simulations on the single-link manipulator demonstrate that themethod achieves accurate trajectory followingwhile maintaining lowcontrol effort.The results further showthat the actor–critic learning mechanism accelerates convergence of the control policy compared with conventional optimization-based strategies.This work highlights the potential of reinforcement learning integrated with optimal control for robotic manipulators and provides a foundation for future extensions to more complex multi-degree-of-freedom systems.The proposed controller is further validated in a physics-based virtual Gazebo environment,demonstrating stable adaptation and real-time feasibility.
基金supported by the Malaysia Ministry of Higher Education under Fundamental Research Grant Scheme with Project Code:FRGS/1/2024/TK07/USM/02/3.
文摘Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This study presents a cognitive control strategy that integrates a Numerical Feedforward Inverse Dynamic Controller(NFIDC)with a Feedback Radial Basis Function Neural Network(FRBFNN).The robot’s mechanical structure was designed in SolidWorks 2022 SP2.0 and validated under operational loads using finite element analysis in ANSYS 2022 R1.The NFIDC-FRBFNN framework merges proactive inverse dynamic compensation with adaptive neural learning to achieve smooth torque responses and accurate motion control.A two-stage simulation evaluation was conducted.In the first stage,the controller was tested in a simulated hospital environment under both ideal and non-ideal conditions.In the second,it was benchmarked against four established controllers-Neural Network Model Reference Adaptive(NNMRA),Z-number Fuzzy Logic(Z-FL),Adaptive Dynamic Controller(ADC),and Fuzzy Logic-PID(FL-PID)—using circular and lemniscate trajectories.Across ten runs,the proposed controller achieved the lowest tracking errors under all conditions.Under ideal conditions,it achieved average improvements of 55.24%,75.75%,and 55.20%in integral absolute error(IAE),integral squared error(ISE),and mean absolute error(MAE),respectively,with coefficient of variation(CV)reductions above 55%.Under non-ideal conditions,average improvements exceeded 64%in IAE,77%in ISE,and 66%in MAE,while maintaining CV reductions above 57%.These results confirm that the NFIDC-FRBFNN controller offers superior accuracy,robustness,and consistency for real-time path tracking in healthcare robotics.
基金supported by the National Natural Science Foundation of China(11272027)
文摘A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of controlling the po- sition and attitude of both the satellite base and the payload grasped by the manipulator end effectors. The equations of motion in reduced-order form for the constrained system are derived by incorporating the constraint equations in terms of accelerations into Kane＇s equations of the unconstrained system. Model analysis shows that the resulting equations perfectly meet the requirement of adaptive controller design. Consequently, by using an indirect approach, an adaptive control scheme is proposed to accomplish position/attitude trajectory tracking control with the uncertain parameters be- ing estimated on-line. The actuator redundancy due to the closed-loop constraints is utilized to minimize a weighted norm of the joint torques. Global asymptotic stability is proven by using Lyapunov＇s method, and simulation results are also presented to demonstrate the effectiveness of the proposed approach.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(class A)(Grant No.XDA22040203)the Fundamental Research Funds for the Central Universities(Grant No.2019XX01)+1 种基金GDNRC[2020]031the Natural Science Foundation of Guangdong Province(Grant No.2020A1515010621).
文摘This paper presents a study on bioinspired closed-loop Central Pattern Generator(CPG)based control of a robot fish for obstacle avoidance and direction tracking.The biomimetic robot fish is made of a rigid head with a pair of pectoral fins,a wire-driven active body covered with soft skin,and a compliant tail.The CPG model consists of four input parameters:the flapping amplitude,the flapping angular velocity,the flapping offset,and the time ratio between the beat phase and the restore phase in flapping.The robot fish is equipped with three infrared sensors mounted on the left,front and right of the robot fish,as well as an inertial measurement unit,from which the surrounding obstacles and moving direction can be sensed.Based on these sensor signals,the closed-loop CPG-based control can drive the robot fish to avoid obstacles and to track designated directions.Four sets of experiments are presented,including avoiding a static obstacle,avoiding a moving obstacle,tracking a designated direction and tracking a designated direction with an obstacle in the path.The experiment results indicated that the presented control strategy worked well and the robot fish can accomplish the obstacle avoidance and direction tracking effectively.
基金Supported by National Natural Science Foundation of China(Grant No.61773060).
文摘Serving the Stewart mechanism as a wheel-legged structure,the most outstanding superiority of the proposed wheel-legged hybrid robot(WLHR)is the active vibration isolation function during rolling on rugged terrain.However,it is difficult to obtain its precise dynamic model,because of the nonlinearity and uncertainty of the heavy robot.This paper presents a dynamic control framework with a decentralized structure for single wheel-leg,position tracking based on model predictive control(MPC)and adaptive impedance module from inside to outside.Through the Newton-Euler dynamic model of the Stewart mechanism,the controller first creates a predictive model by combining Newton-Raphson iteration of forward kinematic and inverse kinematic calculation of Stewart.The actuating force naturally enables each strut to stretch and retract,thereby realizing six degrees-of-freedom(6-DOFs)position-tracking for Stewart wheel-leg.The adaptive impedance control in the outermost loop adjusts environmental impedance parameters by current position and force feedback of wheel-leg along Z-axis.This adjustment allows the robot to adequately control the desired support force tracking,isolating the robot body from vibration that is generated from unknown terrain.The availability of the proposed control methodology on a physical prototype is demonstrated by tracking a Bezier curve and active vibration isolation while the robot is rolling on decelerate strips.By comparing the proportional and integral(PI)and constant impedance controllers,better performance of the proposed algorithm was operated and evaluated through displacement and force sensors internally-installed in each cylinder,as well as an inertial measurement unit(IMU)mounted on the robot body.The proposed algorithm structure significantly enhances the control accuracy and vibration isolation capacity of parallel wheel-legged robot.
基金supported by the National Natural Science Foundation of China(No.12332023)the Zhejiang Provincial Natural Science Foundation of China(No.LY23E050010).
文摘1Introduction To date,in model-based gait-planning methods,the dynamics of the center of mass(COM)of bipedal robots have been analyzed by establishing their linear inverted pendulum model(LIPM)or extended forms(Owaki et al.,2010;Englsberger et al.,2015;Xie et al.,2020).With regard to model-based gait-generation methods for uphill and downhill terrain,Kuo(2007)simulated human gait using an inverted pendulum,which provided a circular trajectory for the COM rather than a horizontal trajectory.He found that a horizontal COM trajectory consumed more muscle energy.Massah et al.(2012)utilized a 3D LIPM and the concept of zero moment point(ZMP).They developed a trajectory planner using the semi-elliptical motion equations of an NAO humanoid robot and simulated walking on various sloped terrains using the Webots platform.
基金Project(51221004)supported by the Science Fund for Creative Research Groups of National Natural Science Foundation of ChinaProject supported by the Program for Zhejiang Leading Team of S&T Innovation,China
文摘The semi-round rigid feet would cause position-posture deviation problem because the actual foothold position is hardly known due to the rolling effect of the semi-round rigid feet during the robot walking. The position-posture deviation problem may harm to the stability and the harmony of the robot, or even makes the robot tip over and fail to walk forward. Focused on the position-posture deviation problem of multi-legged walking robots with semi-round rigid feet, a new method of position-posture closed-loop control is proposed to solve the position-posture deviation problem caused by semi-round rigid feet, based on the inverse velocity kinematics of the multi-legged walking robots. The position-posture closed-loop control is divided into two parts: the position closed-loop control and the posture closed-loop control. Thus, the position-posture control for the robot which is a tight coupling and nonlinear system is decoupled. Co-simulations of position-posture open-loop control and position-posture closed-loop control by MATLAB and ADAMS are implemented, respectively. The co-simulation results verify that the position-posture closed-loop control performs well in solving the position-posture deviation problem caused by semi-round rigid feet.
基金supported by the National Natural Science Foundation of China(62073113,62003122,62303148)the Fundamental Research Funds for the Central Universities(MCCSE2023A01,JZ2023HGTA0201,JZ2023HGQA0109)the Anhui Provincial Natural Science Foundation(2308085QF204)
文摘Dear Editor,This letter considers the formation control of multiple mobile robot systems(MMRS)that only relies on the local observation information.A new distributed finite-time observer is proposed for MMRS under directed graph to estimate the relative information between each follower robot and the leader robot.Then the formation control problem is transformed into the tracking problem and a finite-time tracking controller is proposed based on the robot model feature.
基金supported by the National Natural Science Foundation of China(No.52175259)the 2115 Talent Development Program of China Agricultural University.
文摘Rollover accidents involving agricultural wheeled robots,accompanied by severe mechanical impacts,pose serious threats to operational safety and reduce functional efficiency.To address this issue,an active rollover prevention strategy is proposed,utilizing a single‐gimbal control moment gyro(SGCMG),to stabilize typical agricultural robots and prevent potential rollovers.To match the free oscillation of the pivot front axle,a novel recovery torque model of the coupled robot‐SGCMG system is established,in which two patterns are introduced to refine the rollover process with uncertain parameters.Additionally,a lateral stability index is adopted and analyzed to assess the hazard level of potential rollovers.Aimed at handling uncertain parameters and hazard levels,an adaptive backstepping control strategy is developed for real‐time anti‐rollover implementation.Within this strategy,control gains are adaptively tuned based on theoretical derivations,thereby suppressing rollover tendency while minimizing tuning effort.For verification,a scaled experimental platform,designed according to similarity theory,is constructed to ensure safety of personnel and equipment.Experimental results show that the proposed method can precisely regulate the output torque of the gyro,rapidly and effectively mitigating the risk of imminent rollover.This method provides a promising solution for wheeled robot stability and a theoretical basis for advanced safety control in agricultural robotics.
基金the financial support from the Research Institute for Advanced Manufacturing(RIAM)of The Hong Kong Polytechnic University(project Nos.1-CD9F and 1-CDK3)the Research Grants Council(RGC)of Hong Kong(project Nos.25200424 and 15206223)+2 种基金the GuangDong Basic and Applied Basic Research Foundation(project No.2023A1515110709)the Startup fund(project No.1-BE9L)of the Hong Kong Polytechnic Universitysupported by grant from the Research Committee of the Hong Kong Polytechnic University under student account code RN5Y.
文摘Inspired by bacterial motility mechanisms,Magnetic Helical Miniature Robots(MHMRs)exhibit promising applications in biomedical fields due to their efficient locomotion and compatibility with biological tissues.In this review,we systematically survey the basics of MHMRs,from propulsion mechanism,magnetization and control methods to biomedical applications,aiming to provide readers with an easily understandable overview and fundamental knowledge on implementing MHMRs.The MHMRs are actuated by rotating magnetic fields,achieving steering and rotation through magnetic torque,and converting rotation into forward motion through the helical structure.Magnetization methods for MHMRs are reviewed into three types:attaching magnets,magnetic coatings,and magnetic powder doping.Additionally,this review discusses the control methods for MHMRs,covering imaging techniques,path tracking control—including classical control algorithms and increasingly popular learning-based methods,and swarm control.Subsequently,a comprehensive survey is conducted on the biomedical applications of MHMRs in the treatment of vascular diseases,drug delivery,cell delivery,and their integration with catheters.We finally provide a perspective about future challenges in MHMR research,including enhancing functional design capabilities,developing swarm-assisted independent control mechanisms,refining in vivo imaging techniques,and ensuring robust biocompatibility for safe medical use.
基金supported in part by the National Natural Science Foundationof China under Grant(61801122)Natural Science Foundation of FujianProvince(2022J01542).
文摘The wheeled bipedal robots have great application potential in environments with a mixture of structured and unstructured terrain. However, wheeled bipedal robots have problems such as poor balance ability and low movement level on rough roads. In this paper, a novel and low-cost wheeled bipedal robot with an asymmetrical five-link mechanism is proposed, and the kinematics of the legs and the dynamics of the Wheeled Inverted Pendulum (WIP) are modeled. The primary balance controller of the wheeled bipedal robot is built based on the Linear Quadratic Regulator (LQR) and the compensation method of the virtual pitch angle adjusting the Center of Mass (CoM) position, then the whole-body hybrid torque-position control is established by combining attitude and leg controllers. The stability of the robot’s attitude control and motion is verified with simulations and prototype experiments, which confirm the robot’s ability to pass through complex terrain and resist external interference. The feasibility and reliability of the proposed control model are verified.
基金supported by Liaoning Provincial Department of Education 2023 Basic Research Projects for Universities and Colleges(Grant No.JYTQN2023131)Liaoning Provincial Science and Technology Program:Cooperative Control and Recognition of Unmanned Vessels for Fishing Vessel Operation Scenarios(Grant No.600024003)Liaoning Provincial Department of Education Scientific Research Funding Project(Grant No.LJKZ0726).
文摘This paper proposes a separated trajectory tracking controller for fishing ships at sea state level 6 to solve the trajectory tracking problem of a fishing ship in a 6-level sea state,and to adapt to different working environments and safety requirements.The nonlinear feedback method is used to improve the closed-loop gain shaping algorithm.By introducing the sine function,the problem of excessive control energy of the system can be effectively solved.Moreover,an integral separation design is used to solve the influence of the integral term in conventional PID controllers on the transient performance of the system.In this paper,a common 32.98 m large fiberglass reinforced plastic(FRP)trawler is adopted for simulation research at the winds scale of Beaufort No.7.The results show that the track error is smaller than 3.5 m.The method is safe,feasible,concise and effective and has popularization value in the direction of fishing ship trajectory tracking control.This method can be used to improve the level of informatization and intelligence of fishing ships.
基金supported by the Opening Foundation of China National Logging Corporation(CNLC20229C06)the China Petroleum Technical Service Corporation's science project'Development and application of 475 rotary steering system'(2024T-001001)。
文摘Rotary steering systems(RSSs)have been increasingly used to develop horizontal wells.A static push-the-bit RSS uses three hydraulic modules with varying degrees of expansion and contraction to achieve changes in the pushing force acting on the wellbore in different sizes and directions within a circular range,ultimately allowing the wellbore trajectory to be drilled in a predetermined direction.By analyzing its mathematical principles and the actual characteristics of the instrument,a vector force closed-loop control method,including steering and holding modes,was designed.The adjustment criteria for the three hydraulic modules are determined to achieve rapid adjustment of the vector force.The theoretical feasibility of the developed method was verified by comparing its results with the on-site application data of an imported rotary guidance system.
文摘As robotic surgery provides clinical benefits and increases on a global scale,it also signifies the transition from direct manual control of surgical instruments to digital connectivity and teleoperation.The digital coupling between human control inputs and surgical motion replaces the previous physical link.Robotic surgery is therefore in effect‘surgery-by-wire’,the term capturing the engineering phenomenon that has also occurred in the‘fly-by-wire’of aviation and‘drive-by-wire’of cars.This paper reviews the fundamental commonality across domains.Intrinsic to‘by-wire’control is digital processing,which generates the control signal to the effector.This processing enables a progressive spectrum of motion modulation,from precision and stability of motion,through assistance and envelope protection,to automation.Precision now manifests in all three domains.In modern aircraft and cars,higher-order assistance is commonplace,such as flight envelope protection,with analogous support in driving,as well as significant automation.In robotic surgery,such assistance and automation have not yet entered wider clinical practice,with concepts such as envelope protection requiring further definition.The digital interface combined with telecommunication has also enabled teleoperation in all domains.Therefore,motion‘by-wire’has enhanced performance across industries.A cross-domain perspective will be increasingly useful to facilitate technology transfer and catalyse progress in robotic surgery.As the pan-industry digital transformation evolves,important principles can be derived for application in robotic surgery.
基金supported in part by the National Natural Science Foundation of China under Grant 52575004the Beijing Natural Science Foundation under Grant L243004the National Natural Science Foundation of China under Grant 62403060.
文摘The problem of disturbance rejection in humanoid robots has been properly studied,with most prior work focusing on hip-ankle-stepping compliance control strategies or whole-body inverse dynamics control.This paper presents an adaptive disturbance rejection balance controller based on a Variable-inertia Centroidal Model Predictive Control(ViC-MPC)approach,designed to address both minor disturbances that affect standing balance and major disturbances requiring stepping adjustments.The controller also facilitates reliable balance recovery after stepping adjustments.The humanoid robot is modeled as a spatial variable-inertia ellipsoid,representing the distribution of centroidal dynamics,with the contact wrenches optimized in real-time through a customized MPC formulation.Inspired by capturability-based constraints,we propose an adaptive dynamic stability transition strategy.This strategy is activated based on the Retrospective Horizon Average Centroidal Velocity(RHACV)and the Capture Point(CP),ensuring effective stepping adjustments and disturbance rejection.With the torque-controlled humanoid robot BHR8P,extensive simulation and experimental results demonstrate the effectiveness of the proposed method,highlighting its capability to adapt to and recover from various disturbances with improved stability.
文摘Energy efficiency stands as an essential factor when implementing deep reinforcement learning(DRL)policies for robotic control systems.Standard algorithms,including Deep Deterministic Policy Gradient(DDPG),primarily optimize task rewards but at the cost of excessively high energy consumption,making them impractical for real-world robotic systems.To address this limitation,we propose Physics-Informed DDPG(PI-DDPG),which integrates physics-based energy penalties to develop energy-efficient yet high-performing control policies.The proposed method introduces adaptive physics-informed constraints through a dynamic weighting factor(λ),enabling policies that balance reward maximization with energy savings.Our motivation is to overcome the impracticality of rewardonly optimization by designing controllers that achieve competitive performance while substantially reducing energy consumption.PI-DDPG was evaluated in nine MuJoCo continuous control environments,where it demonstrated significant improvements in energy efficiency without compromising stability or performance.Experimental results confirm that PI-DDPG substantially reduces energy consumption compared to standard DDPG,while maintaining competitive task performance.For instance,energy costs decreased from 5542.98 to 3119.02 in HalfCheetah-v4 and from1909.13 to 1586.75 in Ant-v4,with stable performance in Hopper-v4(205.95 vs.130.82)and InvertedPendulum-v4(322.97 vs.311.29).Although DDPG sometimes yields higher rewards,such as in HalfCheetah-v4(5695.37 vs.4894.59),it requires significantly greater energy expenditure.These results highlight PI-DDPG as a promising energy-conscious alternative for robotic control.
基金supported by the National Natural Science Foundation of China(Grant Nos.62233008 and 51705247)the State Key Laboratory of Mechanics and Control for Aerospace Structures of Nanjing University of Aeronautics and Astronautics.
文摘Autonomous legged robots,capable of navigating uneven terrain,can perform a diverse array of tasks.However,designing locomotion controllers remains challenging.In particular,designing a controller based on durable and reliable proprioceptive sensors,is essential for achieving adaptability.Presently,the controller must either be manually designed for specific robots and tasks,or developed using machine-learning techniques,which require extensive training time and result in complex controllers.Inspired by animal locomotion,we propose a simple yet comprehensive closed-loop modular framework that utilizes minimal proprioceptive feedback(i.e.,the Coxa-Femur(CF)joint angle),enabling a quadruped robot to efficiently navigate unpredictable and uneven terrains,including the step and slope.The framework comprises a basic neural control network capable of rapidly learning optimized motor patterns,and a straightforward module for sensory feedback sharing and integration.In a series of experiments,we show that integrating sensory feedback into the base neural control network aids the robot in continually learning robust motor patterns on flat,step,and slope terrain,compared with the open-loop base framework.Sharing sensory feedback information across the four legs enables a quadruped robot to proactively navigate unpredictable steps with minimal interaction.Furthermore,the controller remains functional even in the absence of sensor signals.This control configuration was successfully transferred to a physical robot without any modifications.
