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
In spite of its intrinsic complexities,the passive gait of bipedal robots on a sloping ramp is a subject of interest for numerous researchers.What distinguishes the present research from similar works is the considera...In spite of its intrinsic complexities,the passive gait of bipedal robots on a sloping ramp is a subject of interest for numerous researchers.What distinguishes the present research from similar works is the consideration of flexibility in the constituent links of this type of robotic systems.This is not a far-fetched assumption because in the transient(impact)phase,due to the impulsive forces which are applied to the system,the likelihood of exciting the vibration modes increases considerably.Moreover,the human leg bones that are involved in walking are supported by viscoelastic muscles and ligaments.Therefore,for achieving more exact results,it is essential to model the robot links with viscoelastic properties.To this end,the Gibbs-Appell formulation and Newton's kinematic impact law are used to derive the most general form of the system's dynamic equations in the swing and transient phases of motion.The most important issue in the passive walking motion of bipedal robots is the determination of the initial robot configuration with which the system could accomplish a periodic and stable gait solely under the effect of gravitational force.The extremely unstable nature of the system studied in this paper and the vibrations caused by the impulsive forces induced by the impact of robot feet with the inclined surface are some of the very serious challenges encountered for achieving the above-mentioned goal.To overcome such challenges,an innovative method that uses a combination of the linearized equations of motion in the swing phase and the algebraic motion equations in the transition phase is presented in this paper to obtain an eigenvalue problem.By solving this problem,the suitable initial conditions that are necessary for the passive gait of this bipedal robot on a sloping surface are determined.The effects of the characteristic parameters of elastic links including the modulus of elasticity and the Kelvin-Voigt coefficient on the walking stability of this type of robotic systems are also studied.The findings of this parametric study reveal that the increase in the Kelvin-Voigt coefficient enhances the stability of the robotic system,while the increase in the modulus of elasticity has an opposite effect.展开更多
In the past few decades,people have been trying to address the issue of walking instability in bipedal robots in uncertain environments.However,most control methods currently have still failed to achieve robust walkin...In the past few decades,people have been trying to address the issue of walking instability in bipedal robots in uncertain environments.However,most control methods currently have still failed to achieve robust walking of bipedal robots under uncertain disturbances.Existing research mostly focuses on motion control methods for robots on uneven terrain and under sudden impact forces,with little consideration for the problem of continuous and intense external force disturbances in uncertain environments.In response to this issue,a disturbance-robust control method based on adaptive feedback compensation is proposed.First,based on the Lagrangian method,the dynamic model of a bipedal robot under different types of external force disturbances was established.Subsequently,through dynamic analysis,it was observed that classical control methods based on hybrid zero dynamics failed to consider the continuous and significant external force disturbances in uncertain environments.Therefore,an adaptive feedback compensation controller was designed,and an adaptive parameter adjustment optimization algorithm was proposed based on walking constraints to achieve stable walking of bipedal robots under different external force disturbances.Finally,in numerical simulation experiments,comparative analysis revealed that using only a controller based on hybrid zero dynamics was insufficient to converge the motion of a planar five-link bipedal robot subjected to periodic forces or bounded noise disturbances to a stable state.In contrast,in the adaptive feedback compensation control method,the use of an adaptive parameter adjustment optimization algorithm to generate time-varying control parameters successfully achieved stable walking of the robot under these disturbances.This indicates the effectiveness of the adaptive parameter adjustment algorithm and the robustness of the adaptive feedback compensation control method.展开更多
Reinforcement learning(RL)provides much potential for locomotion of legged robot.Due to the gap between simulation and the real world,achieving sim-to-real for legged robots is challenging.However,the support polygon ...Reinforcement learning(RL)provides much potential for locomotion of legged robot.Due to the gap between simulation and the real world,achieving sim-to-real for legged robots is challenging.However,the support polygon of legged robots can help to overcome some of these challenges.Quadruped robot has a considerable support polygon,followed by bipedal robot with actuated feet,and point-footed bipedal robot has the smallest support polygon.Therefore,despite the existing sim-to-real gap,most of the recent RL approaches are deployed to the real quadruped robots that are inherently more stable,while the RL-based locomotion of bipedal robot is challenged by zero-shot sim-to-real task.Especially for the point-footed one that gets better dynamic performance,the inevitable tumble brings extra barriers to sim-to-real task.Actually,the crux of this type of problem is the difference of mechanics properties between the physical robot and the simulated one,making it difficult to play the learned skills well on the physical bipedal robot.In this paper,we introduce the embedded mechanics properties(EMP)based on the optimization with Gaussian processes to RL training,making it possible to perform sim-to-real transfer on the BRS1-P robot used in this work,hence the trained policy can be deployed on the BRS1-P without any struggle.We validate the performance of the learning-based BRS1-P on the condition of disturbances and terrains not ever learned,demonstrating the bipedal locomotion and resistant performance.展开更多
In developing and exploring extreme and harsh underwater environments,underwater robots can effectively replace humans to complete tasks.To meet the requirements of underwater flexible motion and comprehensive subsea ...In developing and exploring extreme and harsh underwater environments,underwater robots can effectively replace humans to complete tasks.To meet the requirements of underwater flexible motion and comprehensive subsea operation,a novel octopus-inspired robot with eight soft limbs was designed and developed.This robot possesses the capabilities of underwater bipedal walking,multi-arm swimming,and grasping objects.To closely interact with the underwater seabed environment and minimize disturbance,the robot employs a cable-driven flexible arm for its walking in underwater floor through a bipedal walking mode.The multi-arm swimming offers a means of three-dimensional spatial movement,allowing the robot to swiftly explore and navigate over large areas,thereby enhancing its flexibility.Furthermore,the robot’s walking arm enables it to grasp and transport objects underwater,thereby enhancing its practicality in underwater environments.A simplified motion models and gait generation strategies were proposed for two modes of robot locomotion:swimming and walking,inspired by the movement characteristics of octopus-inspired multi-arm swimming and bipedal walking.Through experimental verification,the robot’s average speed of underwater bipedal walking reaches 7.26 cm/s,while the horizontal movement speed for multi-arm swimming is 8.6 cm/s.展开更多
This paper presents a novel design of minimalist bipedal walking robot with flexible ankle and split-mass balancing systems.The proposed approach implements a novel strategy to achieve stable bipedal walk by decouplin...This paper presents a novel design of minimalist bipedal walking robot with flexible ankle and split-mass balancing systems.The proposed approach implements a novel strategy to achieve stable bipedal walk by decoupling the walking motion control from the sideway balancing control.This strategy allows the walking controller to execute the walking task independently while the sideway balancing controller continuously maintains the balance of the robot.The hip-mass carry approach and selected stages of walk implemented in the control strategy can minimize the efect of major hip mass of the robot on the stability of its walk.In addition,the developed smooth joint trajectory planning eliminates the impacts of feet during the landing.In this paper,the new design of mechanism for locomotion systems and balancing systems are introduced.An additional degree of freedom introduced at the ankle joint increases the sensitivity of the system and response time to the sideway disturbances.The efectiveness of the proposed strategy is experimentally tested on a bipedal robot prototype.The experimental results provide evidence that the proposed strategy is feasible and advantageous.展开更多
Bipedal (Bp) locomotion is one of the most characteristic motor behaviors in human beings. Innate quadrupedal (Qp) four-legged animals also often walk bipedally. The walking posture, however, is significantly differen...Bipedal (Bp) locomotion is one of the most characteristic motor behaviors in human beings. Innate quadrupedal (Qp) four-legged animals also often walk bipedally. The walking posture, however, is significantly different between the two. This suggests that although both have a potential to walk bipedally, however, the human has a body scheme suitable for Bp locomotion, probably its skeletal system. The skeletal system includes the lumbar lordosis, sacral kyphosis, a round pelvis, a large femur neck angle, short feet, and so on. To verify this hypothesis, we compared kinematic and EMG activities between rats and humans during Qp and Bp locomotion on a treadmill belt. The rat is a representative Qp animal, but it is able to acquire Bp walking capability with motor learning. Although the mobile ranges of the hindlimb joint are different during each locomotor pattern between rats and humans, both showed replicable flexion and extension excursion patterns for each joint depending on the locomotor phase. There are many phase-locked EMG bursts between rats and humans during the same walking task and these are observed in the proximal rather than the distal muscles. This suggests that both rats and humans utilize similar neuronal systems for the elaboration of Qp and Bp locomotion. It was interesting that both subjects showed more muscle activities during non-natural locomotor patterns;Qp < Bp for rats and Bp < Qp for humans. This indicates that rat Bp and human Qp walking need more effort and we may be able to find its reason in their skeletal system.展开更多
The ability of bipedal humanoid robots to walk adaptively on varied terrain is a critical challenge for practical applications,drawing substantial attention from academic and industrial research communities in recent ...The ability of bipedal humanoid robots to walk adaptively on varied terrain is a critical challenge for practical applications,drawing substantial attention from academic and industrial research communities in recent years.Traditional model-based locomotion control methods have high modeling complexity,especially in complex terrain environments,making locomotion stability difficult to ensure.Reinforcement learning offers an end-to-end solution for locomotion control in humanoid robots.This approach typically relies solely on proprioceptive sensing to generate control policies,often resulting in increased robot body collisions during practical applications.Excessive collisions can damage the biped robot hardware,and more critically,the absence of multimodal input,such as vision,limits the robot’s ability to perceive environmental context and adjust its gait trajectory promptly.This lack of multimodal perception also hampers stability and robustness during tasks.In this paper,visual information is added to the locomotion control problem of humanoid robot,and a three-stage multi-objective constraint policy distillation optimization algorithm is innovantly proposed.The expert policies of different terrains to meet the requirements of gait aesthetics are trained through reinforcement learning,and these expert policies are distilled into student through policy distillation.Experimental results demonstrate a significant reduction in collision rates when utilizing a control policy that integrates multimodal perception,especially in challenging terrains like stairs,thresholds,and mixed surfaces.This advancement supports the practical deployment of bipedal humanoid robots.展开更多
Jerboas is a lineage of small rodents displaying atypical mouse-like morphology with elongated strong hindlimbs and short forelimbs.They have evolved obligate bipedal saltation and acute senses,and been well-adapted t...Jerboas is a lineage of small rodents displaying atypical mouse-like morphology with elongated strong hindlimbs and short forelimbs.They have evolved obligate bipedal saltation and acute senses,and been well-adapted to vast desert-like habitats.Using a newly sequenced chromosome-scale genome of the Mongolian five-toed jerboa(Orientallactaga sibirica),our comparative genomic analyses and in vitro functional assays showed that the genetic innovations in both protein-coding and non-coding regions played an important role in jerboa morphological and physiological adaptation.Jerboa-specific amino acid substitutions,and segment insertions/deletions(indels)in conserved non-coding elements(CNEs)were found in components of proteoglycan biosynthesis pathway(XYLT1 and CHSY1),which plays an important role in limb development.Meanwhile,we found specific evolutionary changes functionally associated with energy or water metabolism(e.g.,specific amino acid substitutions in ND5 and indels in CNEs physically near ROR2)and senses(e.g.,expansion of vomeronasal receptors and the FAM136A gene family)in jerboas.Further dual-luciferase reporter assay verified that some of the CNEs with jerboa-specific segment indels exerted a significantly different influence on luciferase activity,suggesting changes in their regulatory function in jerboas.Our results revealed the potential molecular mechanisms underlying jerboa adaptation since the divergence from the Eocene-Oligocene transition,and provided more resources and new insights to enhance our understanding of the molecular basis underlying the phenotypic diversity and the environmental adaptation of mammals.展开更多
Some 20 years ago,10-yearold Wang Xingxing watched a documentary that featured a bipedal robot designed by Marc Raibert,now president of U.S.-based robot company Boston Dynamics.That moment planted the seed for his fu...Some 20 years ago,10-yearold Wang Xingxing watched a documentary that featured a bipedal robot designed by Marc Raibert,now president of U.S.-based robot company Boston Dynamics.That moment planted the seed for his future in innovation.Today,operating in China’s private sector,Wang’s company,Hangzhou-based Unitree Robotics in Zhejiang Province,is a globally recognized name in producing high-performance,general-purpose quadruped and humanoid robots.展开更多
This paper presents a control algorithm for push recovery, which particularly focuses on the hip strategy when an external disturbance is applied on the body of a standing under-actuated biped. By analyzing a simplifi...This paper presents a control algorithm for push recovery, which particularly focuses on the hip strategy when an external disturbance is applied on the body of a standing under-actuated biped. By analyzing a simplified dynamic model of a bipedal robot in the stance phase, it is found that horizontal stability can be maintained with a suitably controlled torque applied at the hip. However, errors in the angle or angular velocity of body posture may appear, due to the dynamic coupling of the transla- tional and rotational motions. To solve this problem, different hip strategies are discussed for two cases when （1） external dis- turbance is applied on the center of mass （CoM） and （2） external torque is acting around the CoM, and a universal hip strategy is derived for most disturbances. Moreover, three torque primitives for the hip, depending on the type of disturbance, are designed to achieve translational and rotational balance recovery simultaneously. Compared with closed-loop control, the advantage of the open-loop methods of torque primitives lies in rapid response and reasonable performance. Finally, simulation studies of the push recovery of a bipedal robot are presented to demonstrate the effectiveness of the proposed methods.展开更多
Squatting is a basic movement of bipedal robots,which is essential in robotic actions like jumping or picking up objects.Due to the intrinsic complex dynamics of bipedal robots,perfect squatting motion requires high-p...Squatting is a basic movement of bipedal robots,which is essential in robotic actions like jumping or picking up objects.Due to the intrinsic complex dynamics of bipedal robots,perfect squatting motion requires high-performance motion planning and control algorithms.The standard academic solution combines model predictive control(MPC)with whole-body control(WBC),which is usually computationally expensive and difficult to implement on practical robots with limited computing resources.The real-time kinematic prediction(RKP)method is proposed,which considers upcoming reference motion trajectories and combines it with quadratic programming(QP)-based WBC.Since the WBC handles the full robot dynamics and various constraints,the RKP only needs to adopt the linear kinematics in the robot's task space and to softly constrain the desired accelerations.Then,the computational cost of derived closed-form RKP is greatly reduced.The RKP method is verified in simulation on a heavy-loaded bipedal robot.The robot makes rapid and large-amplitude squatting motions,which require close-to-limit torque outputs.Compared with the conventional QP-based WBC method,the proposed method exhibits high adaptability to rough planning,which implies much less user interference in the robot's motion planning.Furthermore,like the MPC,the proposed method can prepare for upcoming motions in advance but requires much less computation time.展开更多
Walking is the basic locomotion pattern for bipedal robots.The walking pattern is widely generated using the linear inverted pendulum model.The linear inverted pendulum motion of each support period can be designed as...Walking is the basic locomotion pattern for bipedal robots.The walking pattern is widely generated using the linear inverted pendulum model.The linear inverted pendulum motion of each support period can be designed as a walk primitive to be connected to form a walking trajectory.A novel method of integrating double support phase into the walk primitive was proposed in this article.The method describes the generation of walking patterns using walk primitives with double support,specifically for lateral plane including walking in place,walking for lateral,and walking initiation,and for sagittal plane including fixed step length walking,variable step length walking,and walking initiation.Compared to walk primitives without double support phase,those with double support phase reduce the maximum speed required by the robot and eliminate the need to adjust foothold for achieving continuous speed.The performance of the proposed method is validated by simulations and experiments on Neubot,a position-controlled biped robot.展开更多
Significant research interest has recently been attracted to the study of bipedal robots due to the wide variety of their potential applications.In reality,bipedal robots are often required to perform gait transitions...Significant research interest has recently been attracted to the study of bipedal robots due to the wide variety of their potential applications.In reality,bipedal robots are often required to perform gait transitions to achieve flexible walking.In this paper,we consider the gait transition of a five-link underactuated three-dimensional(3 D)bipedal robot,and propose a two-layer control strategy.The strategy consists of a unique,event-based,feedback controller whose feedback gain in each step is updated by an adaptive control law,and a transition controller that guides the robot from the current gait to a neighboring point of the target gait so that the state trajectory can smoothly converge to the target gait.Compared with previous works,the transition controller is parameterized and its control parameters are obtained by solving an optimization problem to guarantee the physical constraints in the transition process.Finally,the effectiveness of the control strategy is illustrated on the underactuated 3 D bipedal robot.展开更多
The wheel-legged biped robot is a typical ground-based mobile robot that can combine the high velocity and high efficiency pertaining to wheeled motion and the strong,obstacle-crossing performance associated with legg...The wheel-legged biped robot is a typical ground-based mobile robot that can combine the high velocity and high efficiency pertaining to wheeled motion and the strong,obstacle-crossing performance associated with legged motion.These robots have gradually exhibited satisfactory application potential in various harsh scenarios such as rubble rescue,military operations,and wilderness exploration.Wheel-legged biped robots are divided into four categories according to the open–close chain structure forms and operation task modes,and the latest technology research status is summarized in this paper.The hardware control system,control method,and application are analyzed,and the dynamic balance control for the two-wheel,biomimetic jumping control for the legs and whole-body control for integrating the wheels and legs are analyzed.In summary,it is observed that the current research exhibits problems,such as the insufficient application of novel materials and a rigid–flexible coupling design;the limited application of the advanced,intelligent control methods;the inadequate understanding of the bionic jumping mechanisms in robot legs;and the insufficient coordination ability of the multi-modal motion,which do not exhibit practical application for the wheel-legged biped robots.Finally,this study discusses the key research directions and development trends for the wheel-legged biped robots.展开更多
Compliance motion and footstep adjustment are active balance control strategies from learning human subconscious behaviors.The force estimation without direct end-actuator force measurement and the optimal footsteps b...Compliance motion and footstep adjustment are active balance control strategies from learning human subconscious behaviors.The force estimation without direct end-actuator force measurement and the optimal footsteps based on complex analytical calculation are still challenging tasks for elementary and kid-size position-controlled robots.In this paper,an online compliant controller with Gravity Projection Observer(GPO),which can express the external force condition of perturbations by the estimated Projection of Gravity(PoG)with estimation covariance,is proposed for the realization of disturbance absorption,with which the robustness of the humanoid contact with environments can be maintained.The fuzzy footstep planner based on capturability analysis is proposed,and the Model Predictive Control(MPC)is applied to generate the desired steps.The fuzzification rules are well-designed and give the corresponding control output responding to complex and changeable external disturbances.To validate the presented methods,a series of experiments on a real humanoid robot are conducted.The results verify the effectiveness of the proposed balance control framework.展开更多
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.
文摘In spite of its intrinsic complexities,the passive gait of bipedal robots on a sloping ramp is a subject of interest for numerous researchers.What distinguishes the present research from similar works is the consideration of flexibility in the constituent links of this type of robotic systems.This is not a far-fetched assumption because in the transient(impact)phase,due to the impulsive forces which are applied to the system,the likelihood of exciting the vibration modes increases considerably.Moreover,the human leg bones that are involved in walking are supported by viscoelastic muscles and ligaments.Therefore,for achieving more exact results,it is essential to model the robot links with viscoelastic properties.To this end,the Gibbs-Appell formulation and Newton's kinematic impact law are used to derive the most general form of the system's dynamic equations in the swing and transient phases of motion.The most important issue in the passive walking motion of bipedal robots is the determination of the initial robot configuration with which the system could accomplish a periodic and stable gait solely under the effect of gravitational force.The extremely unstable nature of the system studied in this paper and the vibrations caused by the impulsive forces induced by the impact of robot feet with the inclined surface are some of the very serious challenges encountered for achieving the above-mentioned goal.To overcome such challenges,an innovative method that uses a combination of the linearized equations of motion in the swing phase and the algebraic motion equations in the transition phase is presented in this paper to obtain an eigenvalue problem.By solving this problem,the suitable initial conditions that are necessary for the passive gait of this bipedal robot on a sloping surface are determined.The effects of the characteristic parameters of elastic links including the modulus of elasticity and the Kelvin-Voigt coefficient on the walking stability of this type of robotic systems are also studied.The findings of this parametric study reveal that the increase in the Kelvin-Voigt coefficient enhances the stability of the robotic system,while the increase in the modulus of elasticity has an opposite effect.
基金supported by the National Natural Science Foundation of China(Grant No.12332003)CIE-Tencent Robotics X Rhino-Bird Focused Research Program,and Zhejiang Provincial Natural Science Foundation of China(Grant No.LY23E050010).
文摘In the past few decades,people have been trying to address the issue of walking instability in bipedal robots in uncertain environments.However,most control methods currently have still failed to achieve robust walking of bipedal robots under uncertain disturbances.Existing research mostly focuses on motion control methods for robots on uneven terrain and under sudden impact forces,with little consideration for the problem of continuous and intense external force disturbances in uncertain environments.In response to this issue,a disturbance-robust control method based on adaptive feedback compensation is proposed.First,based on the Lagrangian method,the dynamic model of a bipedal robot under different types of external force disturbances was established.Subsequently,through dynamic analysis,it was observed that classical control methods based on hybrid zero dynamics failed to consider the continuous and significant external force disturbances in uncertain environments.Therefore,an adaptive feedback compensation controller was designed,and an adaptive parameter adjustment optimization algorithm was proposed based on walking constraints to achieve stable walking of bipedal robots under different external force disturbances.Finally,in numerical simulation experiments,comparative analysis revealed that using only a controller based on hybrid zero dynamics was insufficient to converge the motion of a planar five-link bipedal robot subjected to periodic forces or bounded noise disturbances to a stable state.In contrast,in the adaptive feedback compensation control method,the use of an adaptive parameter adjustment optimization algorithm to generate time-varying control parameters successfully achieved stable walking of the robot under these disturbances.This indicates the effectiveness of the adaptive parameter adjustment algorithm and the robustness of the adaptive feedback compensation control method.
基金supported in part by the National Natural Science Foundation of China under Grant No.62073041,and in part by the“111”Project under Grant B08043.
文摘Reinforcement learning(RL)provides much potential for locomotion of legged robot.Due to the gap between simulation and the real world,achieving sim-to-real for legged robots is challenging.However,the support polygon of legged robots can help to overcome some of these challenges.Quadruped robot has a considerable support polygon,followed by bipedal robot with actuated feet,and point-footed bipedal robot has the smallest support polygon.Therefore,despite the existing sim-to-real gap,most of the recent RL approaches are deployed to the real quadruped robots that are inherently more stable,while the RL-based locomotion of bipedal robot is challenged by zero-shot sim-to-real task.Especially for the point-footed one that gets better dynamic performance,the inevitable tumble brings extra barriers to sim-to-real task.Actually,the crux of this type of problem is the difference of mechanics properties between the physical robot and the simulated one,making it difficult to play the learned skills well on the physical bipedal robot.In this paper,we introduce the embedded mechanics properties(EMP)based on the optimization with Gaussian processes to RL training,making it possible to perform sim-to-real transfer on the BRS1-P robot used in this work,hence the trained policy can be deployed on the BRS1-P without any struggle.We validate the performance of the learning-based BRS1-P on the condition of disturbances and terrains not ever learned,demonstrating the bipedal locomotion and resistant performance.
基金provided by Hy Action Plan Project(Grant no.7172755A)the Key Projects of Science and Technology Plan of Zhejiang Province(Grant no.2019C04018)partially by the Ministry of Science and Higher Education of the Russian Federation as part of the World-class Research Center program:Advanced Digital Technologies(contract No.075-15-2022-312 dated 20.04.2022).
文摘In developing and exploring extreme and harsh underwater environments,underwater robots can effectively replace humans to complete tasks.To meet the requirements of underwater flexible motion and comprehensive subsea operation,a novel octopus-inspired robot with eight soft limbs was designed and developed.This robot possesses the capabilities of underwater bipedal walking,multi-arm swimming,and grasping objects.To closely interact with the underwater seabed environment and minimize disturbance,the robot employs a cable-driven flexible arm for its walking in underwater floor through a bipedal walking mode.The multi-arm swimming offers a means of three-dimensional spatial movement,allowing the robot to swiftly explore and navigate over large areas,thereby enhancing its flexibility.Furthermore,the robot’s walking arm enables it to grasp and transport objects underwater,thereby enhancing its practicality in underwater environments.A simplified motion models and gait generation strategies were proposed for two modes of robot locomotion:swimming and walking,inspired by the movement characteristics of octopus-inspired multi-arm swimming and bipedal walking.Through experimental verification,the robot’s average speed of underwater bipedal walking reaches 7.26 cm/s,while the horizontal movement speed for multi-arm swimming is 8.6 cm/s.
文摘This paper presents a novel design of minimalist bipedal walking robot with flexible ankle and split-mass balancing systems.The proposed approach implements a novel strategy to achieve stable bipedal walk by decoupling the walking motion control from the sideway balancing control.This strategy allows the walking controller to execute the walking task independently while the sideway balancing controller continuously maintains the balance of the robot.The hip-mass carry approach and selected stages of walk implemented in the control strategy can minimize the efect of major hip mass of the robot on the stability of its walk.In addition,the developed smooth joint trajectory planning eliminates the impacts of feet during the landing.In this paper,the new design of mechanism for locomotion systems and balancing systems are introduced.An additional degree of freedom introduced at the ankle joint increases the sensitivity of the system and response time to the sideway disturbances.The efectiveness of the proposed strategy is experimentally tested on a bipedal robot prototype.The experimental results provide evidence that the proposed strategy is feasible and advantageous.
文摘Bipedal (Bp) locomotion is one of the most characteristic motor behaviors in human beings. Innate quadrupedal (Qp) four-legged animals also often walk bipedally. The walking posture, however, is significantly different between the two. This suggests that although both have a potential to walk bipedally, however, the human has a body scheme suitable for Bp locomotion, probably its skeletal system. The skeletal system includes the lumbar lordosis, sacral kyphosis, a round pelvis, a large femur neck angle, short feet, and so on. To verify this hypothesis, we compared kinematic and EMG activities between rats and humans during Qp and Bp locomotion on a treadmill belt. The rat is a representative Qp animal, but it is able to acquire Bp walking capability with motor learning. Although the mobile ranges of the hindlimb joint are different during each locomotor pattern between rats and humans, both showed replicable flexion and extension excursion patterns for each joint depending on the locomotor phase. There are many phase-locked EMG bursts between rats and humans during the same walking task and these are observed in the proximal rather than the distal muscles. This suggests that both rats and humans utilize similar neuronal systems for the elaboration of Qp and Bp locomotion. It was interesting that both subjects showed more muscle activities during non-natural locomotor patterns;Qp < Bp for rats and Bp < Qp for humans. This indicates that rat Bp and human Qp walking need more effort and we may be able to find its reason in their skeletal system.
基金supported by the National Natural Science Foundation of China(U21A20119,62103395,and 51975550).
文摘The ability of bipedal humanoid robots to walk adaptively on varied terrain is a critical challenge for practical applications,drawing substantial attention from academic and industrial research communities in recent years.Traditional model-based locomotion control methods have high modeling complexity,especially in complex terrain environments,making locomotion stability difficult to ensure.Reinforcement learning offers an end-to-end solution for locomotion control in humanoid robots.This approach typically relies solely on proprioceptive sensing to generate control policies,often resulting in increased robot body collisions during practical applications.Excessive collisions can damage the biped robot hardware,and more critically,the absence of multimodal input,such as vision,limits the robot’s ability to perceive environmental context and adjust its gait trajectory promptly.This lack of multimodal perception also hampers stability and robustness during tasks.In this paper,visual information is added to the locomotion control problem of humanoid robot,and a three-stage multi-objective constraint policy distillation optimization algorithm is innovantly proposed.The expert policies of different terrains to meet the requirements of gait aesthetics are trained through reinforcement learning,and these expert policies are distilled into student through policy distillation.Experimental results demonstrate a significant reduction in collision rates when utilizing a control policy that integrates multimodal perception,especially in challenging terrains like stairs,thresholds,and mixed surfaces.This advancement supports the practical deployment of bipedal humanoid robots.
基金supported by the Youth Fund of the National Natural Science Foundation of China(32200345)China Postdoctoral Science Foundation(2022M710878)+2 种基金the National Natural Science Foundation of China(32270453,32270442,31772448)the Key Project of the National Natural Science Foundation of China(32030011)the PI Project of Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou)(GML2021GD0805)。
文摘Jerboas is a lineage of small rodents displaying atypical mouse-like morphology with elongated strong hindlimbs and short forelimbs.They have evolved obligate bipedal saltation and acute senses,and been well-adapted to vast desert-like habitats.Using a newly sequenced chromosome-scale genome of the Mongolian five-toed jerboa(Orientallactaga sibirica),our comparative genomic analyses and in vitro functional assays showed that the genetic innovations in both protein-coding and non-coding regions played an important role in jerboa morphological and physiological adaptation.Jerboa-specific amino acid substitutions,and segment insertions/deletions(indels)in conserved non-coding elements(CNEs)were found in components of proteoglycan biosynthesis pathway(XYLT1 and CHSY1),which plays an important role in limb development.Meanwhile,we found specific evolutionary changes functionally associated with energy or water metabolism(e.g.,specific amino acid substitutions in ND5 and indels in CNEs physically near ROR2)and senses(e.g.,expansion of vomeronasal receptors and the FAM136A gene family)in jerboas.Further dual-luciferase reporter assay verified that some of the CNEs with jerboa-specific segment indels exerted a significantly different influence on luciferase activity,suggesting changes in their regulatory function in jerboas.Our results revealed the potential molecular mechanisms underlying jerboa adaptation since the divergence from the Eocene-Oligocene transition,and provided more resources and new insights to enhance our understanding of the molecular basis underlying the phenotypic diversity and the environmental adaptation of mammals.
文摘Some 20 years ago,10-yearold Wang Xingxing watched a documentary that featured a bipedal robot designed by Marc Raibert,now president of U.S.-based robot company Boston Dynamics.That moment planted the seed for his future in innovation.Today,operating in China’s private sector,Wang’s company,Hangzhou-based Unitree Robotics in Zhejiang Province,is a globally recognized name in producing high-performance,general-purpose quadruped and humanoid robots.
基金Project supported by the National Natural Science Foundation of China （Nos. 51405430 and 61473258） and the National High-Tech R＆D Program （863） of China （No. 2012AA041703）
文摘This paper presents a control algorithm for push recovery, which particularly focuses on the hip strategy when an external disturbance is applied on the body of a standing under-actuated biped. By analyzing a simplified dynamic model of a bipedal robot in the stance phase, it is found that horizontal stability can be maintained with a suitably controlled torque applied at the hip. However, errors in the angle or angular velocity of body posture may appear, due to the dynamic coupling of the transla- tional and rotational motions. To solve this problem, different hip strategies are discussed for two cases when （1） external dis- turbance is applied on the center of mass （CoM） and （2） external torque is acting around the CoM, and a universal hip strategy is derived for most disturbances. Moreover, three torque primitives for the hip, depending on the type of disturbance, are designed to achieve translational and rotational balance recovery simultaneously. Compared with closed-loop control, the advantage of the open-loop methods of torque primitives lies in rapid response and reasonable performance. Finally, simulation studies of the push recovery of a bipedal robot are presented to demonstrate the effectiveness of the proposed methods.
基金Science and Technology Innovation 2030-Key Project,Grant/Award Number:2021ZD0201402。
文摘Squatting is a basic movement of bipedal robots,which is essential in robotic actions like jumping or picking up objects.Due to the intrinsic complex dynamics of bipedal robots,perfect squatting motion requires high-performance motion planning and control algorithms.The standard academic solution combines model predictive control(MPC)with whole-body control(WBC),which is usually computationally expensive and difficult to implement on practical robots with limited computing resources.The real-time kinematic prediction(RKP)method is proposed,which considers upcoming reference motion trajectories and combines it with quadratic programming(QP)-based WBC.Since the WBC handles the full robot dynamics and various constraints,the RKP only needs to adopt the linear kinematics in the robot's task space and to softly constrain the desired accelerations.Then,the computational cost of derived closed-form RKP is greatly reduced.The RKP method is verified in simulation on a heavy-loaded bipedal robot.The robot makes rapid and large-amplitude squatting motions,which require close-to-limit torque outputs.Compared with the conventional QP-based WBC method,the proposed method exhibits high adaptability to rough planning,which implies much less user interference in the robot's motion planning.Furthermore,like the MPC,the proposed method can prepare for upcoming motions in advance but requires much less computation time.
基金supported in part by the National Key R&D Program under Grant 2018YFB1304504.
文摘Walking is the basic locomotion pattern for bipedal robots.The walking pattern is widely generated using the linear inverted pendulum model.The linear inverted pendulum motion of each support period can be designed as a walk primitive to be connected to form a walking trajectory.A novel method of integrating double support phase into the walk primitive was proposed in this article.The method describes the generation of walking patterns using walk primitives with double support,specifically for lateral plane including walking in place,walking for lateral,and walking initiation,and for sagittal plane including fixed step length walking,variable step length walking,and walking initiation.Compared to walk primitives without double support phase,those with double support phase reduce the maximum speed required by the robot and eliminate the need to adjust foothold for achieving continuous speed.The performance of the proposed method is validated by simulations and experiments on Neubot,a position-controlled biped robot.
基金Project supported by the National Natural Science Foundation of China(Nos.91748126,11772292,and 51521064)
文摘Significant research interest has recently been attracted to the study of bipedal robots due to the wide variety of their potential applications.In reality,bipedal robots are often required to perform gait transitions to achieve flexible walking.In this paper,we consider the gait transition of a five-link underactuated three-dimensional(3 D)bipedal robot,and propose a two-layer control strategy.The strategy consists of a unique,event-based,feedback controller whose feedback gain in each step is updated by an adaptive control law,and a transition controller that guides the robot from the current gait to a neighboring point of the target gait so that the state trajectory can smoothly converge to the target gait.Compared with previous works,the transition controller is parameterized and its control parameters are obtained by solving an optimization problem to guarantee the physical constraints in the transition process.Finally,the effectiveness of the control strategy is illustrated on the underactuated 3 D bipedal robot.
基金supported by the Research Fund of State Key Laboratory of Mechanics and Control for Aerospace Structures(1005-IZD23002-25).
文摘The wheel-legged biped robot is a typical ground-based mobile robot that can combine the high velocity and high efficiency pertaining to wheeled motion and the strong,obstacle-crossing performance associated with legged motion.These robots have gradually exhibited satisfactory application potential in various harsh scenarios such as rubble rescue,military operations,and wilderness exploration.Wheel-legged biped robots are divided into four categories according to the open–close chain structure forms and operation task modes,and the latest technology research status is summarized in this paper.The hardware control system,control method,and application are analyzed,and the dynamic balance control for the two-wheel,biomimetic jumping control for the legs and whole-body control for integrating the wheels and legs are analyzed.In summary,it is observed that the current research exhibits problems,such as the insufficient application of novel materials and a rigid–flexible coupling design;the limited application of the advanced,intelligent control methods;the inadequate understanding of the bionic jumping mechanisms in robot legs;and the insufficient coordination ability of the multi-modal motion,which do not exhibit practical application for the wheel-legged biped robots.Finally,this study discusses the key research directions and development trends for the wheel-legged biped robots.
基金supported by the National Natural Science Foundation of China under Grants 62173248,62073245.
文摘Compliance motion and footstep adjustment are active balance control strategies from learning human subconscious behaviors.The force estimation without direct end-actuator force measurement and the optimal footsteps based on complex analytical calculation are still challenging tasks for elementary and kid-size position-controlled robots.In this paper,an online compliant controller with Gravity Projection Observer(GPO),which can express the external force condition of perturbations by the estimated Projection of Gravity(PoG)with estimation covariance,is proposed for the realization of disturbance absorption,with which the robustness of the humanoid contact with environments can be maintained.The fuzzy footstep planner based on capturability analysis is proposed,and the Model Predictive Control(MPC)is applied to generate the desired steps.The fuzzification rules are well-designed and give the corresponding control output responding to complex and changeable external disturbances.To validate the presented methods,a series of experiments on a real humanoid robot are conducted.The results verify the effectiveness of the proposed balance control framework.
