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
介绍了STEP-NC的概念、数据模型及其结构特点,然后通过对比MLP(Machining Line Planner)和STEP-NC数控程序对特征和操作的不同定义方法,分析了在MLP中特征及加工工艺与STEP-NC的对应关系,探讨了在MLP中实现输出STEP-NC格式的零件加工程...介绍了STEP-NC的概念、数据模型及其结构特点,然后通过对比MLP(Machining Line Planner)和STEP-NC数控程序对特征和操作的不同定义方法,分析了在MLP中特征及加工工艺与STEP-NC的对应关系,探讨了在MLP中实现输出STEP-NC格式的零件加工程序的方法。展开更多
As autonomous underwater vehicles(AUVs)merely adopt the inductive obstacle avoidance mechanism to avoid collisions with underwater obstacles,path planners for underwater robots should consider the poor search efficien...As autonomous underwater vehicles(AUVs)merely adopt the inductive obstacle avoidance mechanism to avoid collisions with underwater obstacles,path planners for underwater robots should consider the poor search efficiency and inadequate collision-avoidance ability.To overcome these problems,a specific two-player path planner based on an improved algorithm is designed.First,by combing the artificial attractive field(AAF)of artificial potential field(APF)approach with the random rapidly exploring tree(RRT)algorithm,an improved AAF-RRT algorithm with a changing attractive force proportional to the Euler distance between the point to be extended and the goal point is proposed.Second,a twolayer path planner is designed with path smoothing,which combines global planning and local planning.Finally,as verified by the simulations,the improved AAF-RRT algorithm has the strongest searching ability and the ability to cross the narrow passage among the studied three algorithms,which are the basic RRT algorithm,the common AAF-RRT algorithm,and the improved AAF-RRT algorithm.Moreover,the two-layer path planner can plan a global and optimal path for AUVs if a sudden obstacle is added to the simulation environment.展开更多
Driving style,traffic and weather conditions have a significant impact on vehicle fuel consumption and in particular,the road freight traffic significantly contributes to the CO2 increase in atmosphere.This paper prop...Driving style,traffic and weather conditions have a significant impact on vehicle fuel consumption and in particular,the road freight traffic significantly contributes to the CO2 increase in atmosphere.This paper proposes an Eco-Route Planner devoted to determine and communicate to the drivers of Heavy-Duty Vehicles(HDVs)the eco-route that guarantees the minimum fuel consumption by respecting the travel time established by the freight companies.The proposed eco-route is the optimal route from origin to destination and includes the optimized speed and gear profiles.To this aim,the Cloud Computing System architecture is composed of two main components:the Data Management System that collects,fuses and integrates the raw external sources data and the Cloud Optimizer that builds the route network,selects the eco-route and determines the optimal speed and gear profiles.Finally,a real case study is discussed by showing the benefit of the proposed Eco-Route planner.展开更多
It is necessary for legged robots to walk stably and smoothly on rough terrain.In this paper,a desired landing points(DLP) walking method based on preview control was proposed in which an off-line foot motion trace an...It is necessary for legged robots to walk stably and smoothly on rough terrain.In this paper,a desired landing points(DLP) walking method based on preview control was proposed in which an off-line foot motion trace and an on-line modification of the trace were used to enable the robot to walk on rough terrain.The on-line modification was composed of speed modification,foot lifting-off height modification,step length modification,and identification and avoidance of unsuitable landing terrain.A planner quadruped robot simulator was used to apply the DLP walking method.The correctness of the method was proven by a series of simulations using the Adams and Simulink.展开更多
Mobile manipulators are used in a variety of fields because of their flexibility and maneuverability.The path planning capability of the mobile manipulator is one of the important indicators to evaluate the performanc...Mobile manipulators are used in a variety of fields because of their flexibility and maneuverability.The path planning capability of the mobile manipulator is one of the important indicators to evaluate the performance of the manipulator,but it is greatly challenged in the face of maps with narrow channel.To address the problem,an improved hierarchical motion planner(IHMP)is proposed,which consists of a two-dimensional(2D)path planner for the mobile base,and a three-dimensional(3D)trajectory planner for the on-board manipulator.Firstly,a hybrid sampling strategy is proposed,which can reduce invalid nodes of the generated probabilistic roadmap.Bridge test is used to locate the narrow channel areas,and a Gaussian sampler is deployed in these areas and the boundaries.Meanwhile,a random sampler is deployed in the rest areas.Trajectory planner for on-board manipulator is to generate a collision-free and safe trajectory in the narrow channel with collaboration of the 2D path planner.The experimental results show that IHMP is effective for mobile manipulator motion planning in complex static environments,especially in narrow channel.展开更多
An efficient algorithm for path planning is crucial for guiding autonomous surface vehicles(ASVs)through designated waypoints.However,current evaluations of ASV path planning mainly focus on comparing total path lengt...An efficient algorithm for path planning is crucial for guiding autonomous surface vehicles(ASVs)through designated waypoints.However,current evaluations of ASV path planning mainly focus on comparing total path lengths,using temporal models to estimate travel time,idealized integration of global and local motion planners,and omission of external environmental disturbances.These rudimentary criteria cannot adequately capture real-world operations.To address these shortcomings,this study introduces a simulation framework for evaluating navigation modules designed for ASVs.The proposed framework is implemented on a prototype ASV using the Robot Operating System(ROS)and the Gazebo simulation platform.The implementation processes replicated satellite images with the extended Kalman filter technique to acquire localized location data.Cost minimization for global trajectories is achieved through the application of Dijkstra and A*algorithms,while local obstacle avoidance is managed by the dynamic window approach algorithm.The results demonstrate the distinctions and intricacies of the metrics provided by the proposed simulation framework compared with the rudimentary criteria commonly utilized in conventional path planning works.展开更多
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.
基金Supported by Zhejiang Key R&D Program 558 No.2021C03157the“Construction of a Leading Innovation Team”project by the Hangzhou Munic-559 ipal government,the Startup funding of New-joined PI of Westlake University with Grant No.560(041030150118)the funding support from the Westlake University and Bright Dream Joint In-561 stitute for Intelligent Robotics.
文摘As autonomous underwater vehicles(AUVs)merely adopt the inductive obstacle avoidance mechanism to avoid collisions with underwater obstacles,path planners for underwater robots should consider the poor search efficiency and inadequate collision-avoidance ability.To overcome these problems,a specific two-player path planner based on an improved algorithm is designed.First,by combing the artificial attractive field(AAF)of artificial potential field(APF)approach with the random rapidly exploring tree(RRT)algorithm,an improved AAF-RRT algorithm with a changing attractive force proportional to the Euler distance between the point to be extended and the goal point is proposed.Second,a twolayer path planner is designed with path smoothing,which combines global planning and local planning.Finally,as verified by the simulations,the improved AAF-RRT algorithm has the strongest searching ability and the ability to cross the narrow passage among the studied three algorithms,which are the basic RRT algorithm,the common AAF-RRT algorithm,and the improved AAF-RRT algorithm.Moreover,the two-layer path planner can plan a global and optimal path for AUVs if a sudden obstacle is added to the simulation environment.
基金the European Project opti Truck(optimal fuel consumption with predictive power train control and calibration for intelligent Truck)of the H2020 innovation programme。
文摘Driving style,traffic and weather conditions have a significant impact on vehicle fuel consumption and in particular,the road freight traffic significantly contributes to the CO2 increase in atmosphere.This paper proposes an Eco-Route Planner devoted to determine and communicate to the drivers of Heavy-Duty Vehicles(HDVs)the eco-route that guarantees the minimum fuel consumption by respecting the travel time established by the freight companies.The proposed eco-route is the optimal route from origin to destination and includes the optimized speed and gear profiles.To this aim,the Cloud Computing System architecture is composed of two main components:the Data Management System that collects,fuses and integrates the raw external sources data and the Cloud Optimizer that builds the route network,selects the eco-route and determines the optimal speed and gear profiles.Finally,a real case study is discussed by showing the benefit of the proposed Eco-Route planner.
基金supported in part by the National Natural Science Foundation of China under Grant 60875067the Natural Science Foundation of Heilongjiang Province under Grant F200602the Technical Innovation Talent Foundation of Harbin under Grant 2010RFQXG010
文摘It is necessary for legged robots to walk stably and smoothly on rough terrain.In this paper,a desired landing points(DLP) walking method based on preview control was proposed in which an off-line foot motion trace and an on-line modification of the trace were used to enable the robot to walk on rough terrain.The on-line modification was composed of speed modification,foot lifting-off height modification,step length modification,and identification and avoidance of unsuitable landing terrain.A planner quadruped robot simulator was used to apply the DLP walking method.The correctness of the method was proven by a series of simulations using the Adams and Simulink.
文摘Mobile manipulators are used in a variety of fields because of their flexibility and maneuverability.The path planning capability of the mobile manipulator is one of the important indicators to evaluate the performance of the manipulator,but it is greatly challenged in the face of maps with narrow channel.To address the problem,an improved hierarchical motion planner(IHMP)is proposed,which consists of a two-dimensional(2D)path planner for the mobile base,and a three-dimensional(3D)trajectory planner for the on-board manipulator.Firstly,a hybrid sampling strategy is proposed,which can reduce invalid nodes of the generated probabilistic roadmap.Bridge test is used to locate the narrow channel areas,and a Gaussian sampler is deployed in these areas and the boundaries.Meanwhile,a random sampler is deployed in the rest areas.Trajectory planner for on-board manipulator is to generate a collision-free and safe trajectory in the narrow channel with collaboration of the 2D path planner.The experimental results show that IHMP is effective for mobile manipulator motion planning in complex static environments,especially in narrow channel.
基金Supported by the funding from RMIT Internal Research Grant R1.
文摘An efficient algorithm for path planning is crucial for guiding autonomous surface vehicles(ASVs)through designated waypoints.However,current evaluations of ASV path planning mainly focus on comparing total path lengths,using temporal models to estimate travel time,idealized integration of global and local motion planners,and omission of external environmental disturbances.These rudimentary criteria cannot adequately capture real-world operations.To address these shortcomings,this study introduces a simulation framework for evaluating navigation modules designed for ASVs.The proposed framework is implemented on a prototype ASV using the Robot Operating System(ROS)and the Gazebo simulation platform.The implementation processes replicated satellite images with the extended Kalman filter technique to acquire localized location data.Cost minimization for global trajectories is achieved through the application of Dijkstra and A*algorithms,while local obstacle avoidance is managed by the dynamic window approach algorithm.The results demonstrate the distinctions and intricacies of the metrics provided by the proposed simulation framework compared with the rudimentary criteria commonly utilized in conventional path planning works.
