Motion planning is critical to realize the autonomous operation of mobile robots.As the complexity and randomness of robot application scenarios increase,the planning capability of the classical hierarchical motion pl...Motion planning is critical to realize the autonomous operation of mobile robots.As the complexity and randomness of robot application scenarios increase,the planning capability of the classical hierarchical motion planners is challenged.With the development of machine learning,the deep reinforcement learning(DRL)-based motion planner has gradually become a research hotspot due to its several advantageous feature.The DRL-based motion planner is model-free and does not rely on the prior structured map.Most importantly,the DRL-based motion planner achieves the unification of the global planner and the local planner.In this paper,we provide a systematic review of various motion planning methods.Firstly,we summarize the representative and state-of-the-art works for each submodule of the classical motion planning architecture and analyze their performance features.Then,we concentrate on summarizing reinforcement learning(RL)-based motion planning approaches,including motion planners combined with RL improvements,map-free RL-based motion planners,and multi-robot cooperative planning methods.Finally,we analyze the urgent challenges faced by these mainstream RLbased motion planners in detail,review some state-of-the-art works for these issues,and propose suggestions for future research.展开更多
This paper presents an effective way to support motion planning of legged mobile robots—Inverted Modelling,based on the equivalent metamorphic mechanism concept.The difference from the previous research is that we he...This paper presents an effective way to support motion planning of legged mobile robots—Inverted Modelling,based on the equivalent metamorphic mechanism concept.The difference from the previous research is that we herein invert the equivalent parallel mechanism.Assuming the leg mechanisms are hybrid links,the body of robot being considered as fixed platform,and ground as moving platform.The motion performance is transformed and measured in the body frame.Terrain and joint limits are used as input parameters to the model,resulting in the representation which is independent of terrains and particular poses in Inverted Modelling.Hence,it can universally be applied to any kind of legged robots as global motion performance framework.Several performance measurements using Inverted Modelling are presented and used in motion performance evaluation.According to the requirements of actual work like motion continuity and stability,motion planning of legged robot can be achieved using different measurements on different terrains.Two cases studies present the simulations of quadruped and hexapod robots walking on rugged roads.The results verify the correctness and effectiveness of the proposed method.展开更多
Presents the mobile robots dynamic motion planning problem with a task to find an obstacle free route that requires minimum travel time from the start point to the destination point in a changing environment, due to t...Presents the mobile robots dynamic motion planning problem with a task to find an obstacle free route that requires minimum travel time from the start point to the destination point in a changing environment, due to the obstacle’s moving. An Genetic Algorithm fuzzy (GA Fuzzy) based optimal approach proposed to find any obstacle free path and the GA used to select the optimal one, points out that using this learned knowledge off line, a mobile robot can navigate to its goal point when it faces new scenario on line. Concludes with the optimal rule base given and the simulation results showing its effectiveness.展开更多
Many applications above the capability of a single robot need the cooperation of multiple mobile robots, but effective cooperation is hard to achieve. In this paper, a master slave method is proposed to control the m...Many applications above the capability of a single robot need the cooperation of multiple mobile robots, but effective cooperation is hard to achieve. In this paper, a master slave method is proposed to control the motions of multiple mobile robots that cooperatively transport a common object from a start point to a goal point. A noholonomic kinematic model to constrain the motions of multiple mobile robots is built in order to achieve cooperative motions of them, and a “Dynamic Coordinator” strategy is used to deal with the collision avoidance of the master robot and slave robot individually. Simulation results show the robustness and effectiveness of the method.展开更多
Continuum manipulators have important applications in the human–machine interaction fields.The kinematics,dynamics,and control issues of the continuum manipulators are rather different from a conventional rigid-link ...Continuum manipulators have important applications in the human–machine interaction fields.The kinematics,dynamics,and control issues of the continuum manipulators are rather different from a conventional rigid-link manipulator.By the aid of Lie groups theory and exponential coordinate representations,the kinematics of the continuum manipulators with piecewise constant curvatures and actuated by tendons is investigated in this paper.On the basis of differential kinematics analysis,the complete Jacobian of the continuum manipulators is derived analytically,and then a new motion planning approach,named as“dynamic coordination method”is presented for the multisegments continuum manipulators,which is a class of superredundant manipulators.The novel motion planning approach is featured by some appealing properties,and the feasibility of the modeling and the motion planning method is demonstrated by some numerical simulations.展开更多
Navigation of autonomous mobile robots in dynamic and unknown environments needs to take into account different kinds of uncertainties. Type-1 fuzzy logic research has been largely used in the control of mobile robots...Navigation of autonomous mobile robots in dynamic and unknown environments needs to take into account different kinds of uncertainties. Type-1 fuzzy logic research has been largely used in the control of mobile robots. However, type-1 fuzzy control presents limitations in handling those uncertainties as it uses precise fuzzy sets. Indeed type-1 fuzzy sets cannot deal with linguistic and numerical uncertainties associated with either the mechanical aspect of robots, or with dynamic changing environment or with knowledge used in the phase of conception of a fuzzy system. Recently many researchers have applied type-2 fuzzy logic to improve performance. As control using type-2 fuzzy sets represents a new generation of fuzzy controllers in mobile robotic issue, it is interesting to present the performances that can offer type-2 fuzzy sets by regards to type-1 fuzzy sets. The paper presented deep and new comparisons between the two sides of fuzzy logic and demonstrated the great interest in controlling mobile robot using type-2 fuzzy logic. We deal with the design of new controllers for mobile robots using type-2 fuzzy logic in the navigation process in unknown and dynamic environments. The dynamicity of the environment is depicted by the presence of other dynamic robots. The performances of the proposed controllers are represented by both simulations and experimental results, and discussed over graphical paths and numerical analysis.展开更多
Safe and effective autonomous navigation in dynamic environments is challenging for four-wheel independently driven steered mobile robots(FWIDSMRs)due to the flexible allocation of multiple maneuver modes.To address t...Safe and effective autonomous navigation in dynamic environments is challenging for four-wheel independently driven steered mobile robots(FWIDSMRs)due to the flexible allocation of multiple maneuver modes.To address this problem,this study proposes a novel multiple mode-based navigation system,which can achieve efficient motion planning and accurate tracking control.To reduce the calculation burden and obtain a comprehensive optimized global path,a kinodynamic interior-exterior cell exploration planning method,which leverages the hybrid space of available modes with an incorporated exploration guiding algorithm,is designed.By utilizing the sampled subgoals and the constructed global path,local planning is then performed to avoid unexpected obstacles and potential collisions.With the desired profile curvature and preselected mode,a fuzzy adaptive receding horizon control is proposed such that the online updating of the predictive horizon is realized to enhance the trajectory-following precision.The tracking controller design is achieved using the quadratic programming(QP)technique,and the primal-dual neural network optimization technique is used to solve the QP problem.Experimental results on a real-time FWIDSMR validate that the proposed method shows superior features over some existing methods in terms of efficiency and accuracy.展开更多
Artificial coordinating fields (ACF) are proposed to deal with the motion planning problems of mobile robots in uncertain dynamic environments. An ACF around an obstacle can generate two orthogonal force vectors to a ...Artificial coordinating fields (ACF) are proposed to deal with the motion planning problems of mobile robots in uncertain dynamic environments. An ACF around an obstacle can generate two orthogonal force vectors to a robot: one is called the coordinating force vector which is purposively designed in this paper, and the other is the repulsive force vector which is the same as that in a conventional artificial potential field. The ACF is designed according to the updated motion purpose and the relative states of the robot with respect to its local environment, and it also satisfies the robot’s dynamic constraints. The direction of the coordinating force can be determiend on line according to an optimal evaluation function. The ACF can effectively remove the local minima, and reduce the oscillation of the planned trajectory between multiple obstacles. Only local knowledge of the environments is needed in the ACF-based motion planning. The properties of the ACF such as controllability, adaptability, safety and reachability are studied and discussed in detail in this paper. Theoretical analysis and simulations are given to illustrate our main results.展开更多
针对快速扩展随机树(rapidly exploring random tree,RRT)算法在移动机器人路径规划过程中存在盲目搜索、内存计算量大和冗余点较多等问题,提出了改进的RRT算法。首先,随机点进行扩展时引入动态目标采样率,引导随机点向目标点方向扩展;...针对快速扩展随机树(rapidly exploring random tree,RRT)算法在移动机器人路径规划过程中存在盲目搜索、内存计算量大和冗余点较多等问题,提出了改进的RRT算法。首先,随机点进行扩展时引入动态目标采样率,引导随机点向目标点方向扩展;其次,融合A*算法中代价函数策略,在加入不同权重因子之后,选取代价值合适的节点作为待扩展节点;然后,针对初始路径过长并存在过多冗余点的问题,提出反向搜索剪枝方法,对裁剪后的路径进行三次样条插值平滑处理来改善路径质量;最后,利用Pycharm对改进的RRT算法进行仿真验证。仿真结果表明,改进的RRT算法相较于传统RRT算法、RRT*算法和基于概率P的RRT算法(P-RRT),在路径的规划长度、规划时间和扩展节点数上都具有明显优势,提高了机器人的路径规划效率。展开更多
基金supported by the National Natural Science Foundation of China (62173251)the“Zhishan”Scholars Programs of Southeast University+1 种基金the Fundamental Research Funds for the Central UniversitiesShanghai Gaofeng&Gaoyuan Project for University Academic Program Development (22120210022)
文摘Motion planning is critical to realize the autonomous operation of mobile robots.As the complexity and randomness of robot application scenarios increase,the planning capability of the classical hierarchical motion planners is challenged.With the development of machine learning,the deep reinforcement learning(DRL)-based motion planner has gradually become a research hotspot due to its several advantageous feature.The DRL-based motion planner is model-free and does not rely on the prior structured map.Most importantly,the DRL-based motion planner achieves the unification of the global planner and the local planner.In this paper,we provide a systematic review of various motion planning methods.Firstly,we summarize the representative and state-of-the-art works for each submodule of the classical motion planning architecture and analyze their performance features.Then,we concentrate on summarizing reinforcement learning(RL)-based motion planning approaches,including motion planners combined with RL improvements,map-free RL-based motion planners,and multi-robot cooperative planning methods.Finally,we analyze the urgent challenges faced by these mainstream RLbased motion planners in detail,review some state-of-the-art works for these issues,and propose suggestions for future research.
基金National Natural Science Foundation of China(Grant No.51735009)。
文摘This paper presents an effective way to support motion planning of legged mobile robots—Inverted Modelling,based on the equivalent metamorphic mechanism concept.The difference from the previous research is that we herein invert the equivalent parallel mechanism.Assuming the leg mechanisms are hybrid links,the body of robot being considered as fixed platform,and ground as moving platform.The motion performance is transformed and measured in the body frame.Terrain and joint limits are used as input parameters to the model,resulting in the representation which is independent of terrains and particular poses in Inverted Modelling.Hence,it can universally be applied to any kind of legged robots as global motion performance framework.Several performance measurements using Inverted Modelling are presented and used in motion performance evaluation.According to the requirements of actual work like motion continuity and stability,motion planning of legged robot can be achieved using different measurements on different terrains.Two cases studies present the simulations of quadruped and hexapod robots walking on rugged roads.The results verify the correctness and effectiveness of the proposed method.
文摘Presents the mobile robots dynamic motion planning problem with a task to find an obstacle free route that requires minimum travel time from the start point to the destination point in a changing environment, due to the obstacle’s moving. An Genetic Algorithm fuzzy (GA Fuzzy) based optimal approach proposed to find any obstacle free path and the GA used to select the optimal one, points out that using this learned knowledge off line, a mobile robot can navigate to its goal point when it faces new scenario on line. Concludes with the optimal rule base given and the simulation results showing its effectiveness.
文摘Many applications above the capability of a single robot need the cooperation of multiple mobile robots, but effective cooperation is hard to achieve. In this paper, a master slave method is proposed to control the motions of multiple mobile robots that cooperatively transport a common object from a start point to a goal point. A noholonomic kinematic model to constrain the motions of multiple mobile robots is built in order to achieve cooperative motions of them, and a “Dynamic Coordinator” strategy is used to deal with the collision avoidance of the master robot and slave robot individually. Simulation results show the robustness and effectiveness of the method.
基金supported by the National Key R&D Program of China under Grant 2019YFB1309603the Natural Science Foundation of China under Grants 51775002 and 11702294+2 种基金the Natural Science Foundation of Beijing under Grants L172001,4204097,3172009,and 3194047the Joint Program of Beijing Municipal Foundation and Education Commission under Grant KZ202010009015the Scientific Research Foundation of North China University of Technology.
文摘Continuum manipulators have important applications in the human–machine interaction fields.The kinematics,dynamics,and control issues of the continuum manipulators are rather different from a conventional rigid-link manipulator.By the aid of Lie groups theory and exponential coordinate representations,the kinematics of the continuum manipulators with piecewise constant curvatures and actuated by tendons is investigated in this paper.On the basis of differential kinematics analysis,the complete Jacobian of the continuum manipulators is derived analytically,and then a new motion planning approach,named as“dynamic coordination method”is presented for the multisegments continuum manipulators,which is a class of superredundant manipulators.The novel motion planning approach is featured by some appealing properties,and the feasibility of the modeling and the motion planning method is demonstrated by some numerical simulations.
文摘Navigation of autonomous mobile robots in dynamic and unknown environments needs to take into account different kinds of uncertainties. Type-1 fuzzy logic research has been largely used in the control of mobile robots. However, type-1 fuzzy control presents limitations in handling those uncertainties as it uses precise fuzzy sets. Indeed type-1 fuzzy sets cannot deal with linguistic and numerical uncertainties associated with either the mechanical aspect of robots, or with dynamic changing environment or with knowledge used in the phase of conception of a fuzzy system. Recently many researchers have applied type-2 fuzzy logic to improve performance. As control using type-2 fuzzy sets represents a new generation of fuzzy controllers in mobile robotic issue, it is interesting to present the performances that can offer type-2 fuzzy sets by regards to type-1 fuzzy sets. The paper presented deep and new comparisons between the two sides of fuzzy logic and demonstrated the great interest in controlling mobile robot using type-2 fuzzy logic. We deal with the design of new controllers for mobile robots using type-2 fuzzy logic in the navigation process in unknown and dynamic environments. The dynamicity of the environment is depicted by the presence of other dynamic robots. The performances of the proposed controllers are represented by both simulations and experimental results, and discussed over graphical paths and numerical analysis.
基金The work was funded in part by the Guangdong Major Science and Technology Project,China(Grant Nos.2019B090919003 and 2017B090913001)in part by the China Postdoctoral Science Foundation(Grant No.2019M650179)+2 种基金in part by the Guangdong Innovative and Entrepreneurial Research Team Program,China(Grant No.2019ZT08Z780)in part by the Dongguan Innovative Research Team Program,China(Grant No.201536000100031)in part by the Guangdong HUST Industrial Technology Research Institute,Guangdong Provincial Key Laboratory of Manufacturing Equipment Digitization,China(Grant No.2020B1212060014).
文摘Safe and effective autonomous navigation in dynamic environments is challenging for four-wheel independently driven steered mobile robots(FWIDSMRs)due to the flexible allocation of multiple maneuver modes.To address this problem,this study proposes a novel multiple mode-based navigation system,which can achieve efficient motion planning and accurate tracking control.To reduce the calculation burden and obtain a comprehensive optimized global path,a kinodynamic interior-exterior cell exploration planning method,which leverages the hybrid space of available modes with an incorporated exploration guiding algorithm,is designed.By utilizing the sampled subgoals and the constructed global path,local planning is then performed to avoid unexpected obstacles and potential collisions.With the desired profile curvature and preselected mode,a fuzzy adaptive receding horizon control is proposed such that the online updating of the predictive horizon is realized to enhance the trajectory-following precision.The tracking controller design is achieved using the quadratic programming(QP)technique,and the primal-dual neural network optimization technique is used to solve the QP problem.Experimental results on a real-time FWIDSMR validate that the proposed method shows superior features over some existing methods in terms of efficiency and accuracy.
基金the National Natural Science Foundation of China (Grant Nos. 60131160741 , 60334010).
文摘Artificial coordinating fields (ACF) are proposed to deal with the motion planning problems of mobile robots in uncertain dynamic environments. An ACF around an obstacle can generate two orthogonal force vectors to a robot: one is called the coordinating force vector which is purposively designed in this paper, and the other is the repulsive force vector which is the same as that in a conventional artificial potential field. The ACF is designed according to the updated motion purpose and the relative states of the robot with respect to its local environment, and it also satisfies the robot’s dynamic constraints. The direction of the coordinating force can be determiend on line according to an optimal evaluation function. The ACF can effectively remove the local minima, and reduce the oscillation of the planned trajectory between multiple obstacles. Only local knowledge of the environments is needed in the ACF-based motion planning. The properties of the ACF such as controllability, adaptability, safety and reachability are studied and discussed in detail in this paper. Theoretical analysis and simulations are given to illustrate our main results.
文摘针对快速扩展随机树(rapidly exploring random tree,RRT)算法在移动机器人路径规划过程中存在盲目搜索、内存计算量大和冗余点较多等问题,提出了改进的RRT算法。首先,随机点进行扩展时引入动态目标采样率,引导随机点向目标点方向扩展;其次,融合A*算法中代价函数策略,在加入不同权重因子之后,选取代价值合适的节点作为待扩展节点;然后,针对初始路径过长并存在过多冗余点的问题,提出反向搜索剪枝方法,对裁剪后的路径进行三次样条插值平滑处理来改善路径质量;最后,利用Pycharm对改进的RRT算法进行仿真验证。仿真结果表明,改进的RRT算法相较于传统RRT算法、RRT*算法和基于概率P的RRT算法(P-RRT),在路径的规划长度、规划时间和扩展节点数上都具有明显优势,提高了机器人的路径规划效率。