A neural-network-based motion controller in task space is presented in this paper.The proposed controller is addressed as a two-loop cascade control scheme.The outer loop is given by kinematic control in the task spac...A neural-network-based motion controller in task space is presented in this paper.The proposed controller is addressed as a two-loop cascade control scheme.The outer loop is given by kinematic control in the task space.It provides a joint velocity reference signal to the inner one.The inner loop implements a velocity servo loop at the robot joint level.A radial basis function network(RBFN)is integrated with proportional-integral(PI)control to construct a velocity tracking control scheme for the inner loop.Finally,a prototype technology based control system is designed for a robotic manipulator.The proposed control scheme is applied to the robotic manipulator.Experimental results confirm the validity of the proposed control scheme by comparing it with other control strategies.展开更多
Trajectory tracking control of space robots in task space is of great importance to space missions, which require on-orbit manipulations. This paper focuses on position and attitude tracking control of a tree-floating...Trajectory tracking control of space robots in task space is of great importance to space missions, which require on-orbit manipulations. This paper focuses on position and attitude tracking control of a tree-floating space robot in task space. Since nei- ther the nonlinear terms and parametric uncertainties of the dynamic model, nor the external disturbances are known, an adap- tive radial basis function network based nonsingular terminal sliding mode （RBF-NTSM） control method is presented. The proposed algorithm combines the nonlinear sliding manifold with the radial basis function to improve control performance. Moreover, in order to account for actuator physical constraints, a constrained adaptive RBF-NTSM, which employs a RBF network to compensate for the limited input is developed. The adaptive updating laws acquired by Lyapunov approach guar- antee the global stability of the control system and suppress chattering problems. Two examples are provided using a six-link free-floating space robot. Simulation results clearly demonstrate that the proposed constrained adaptive RBF-NTSM control method performs high precision task based on incomplete dynamic model of the space robots. In addition, the control errors converge faster and the chattering is eliminated comparing to traditional sliding mode control.展开更多
This paper deals with a flexible macro-micro manipulator system, which includes a long flexible manipulator and a relatively short rigid manipulator attached to the tip of the macro manipulator. A flexible macro manip...This paper deals with a flexible macro-micro manipulator system, which includes a long flexible manipulator and a relatively short rigid manipulator attached to the tip of the macro manipulator. A flexible macro manipulator possesses the advantages of wide operating range, high speed, and low energy consumption, but the disadvantage of a low tracking precision. The macro-micro manipulator system improves tracking performance by compensating for the endpoint tracking error while maintaining the advantages of the flexible macro manipulator. A trajectory planning scheme was built utilizing the task space division method. The division point is chosen to optimize the error compensation and energy consumption for the whole system. Then movements of the macro-micro manipulator can be determined using separate inverse kinematic models. Simulation results for a planar 4-DOF macro-micro manipulator system are presented to show the effectiveness of the control system.展开更多
As a well-explored template that captures the essential dynamical behaviors of legged locomotion on sagittal plane,the spring-loaded inverted pendulum(SLIP)model has been extensively employed in both biomechanical stu...As a well-explored template that captures the essential dynamical behaviors of legged locomotion on sagittal plane,the spring-loaded inverted pendulum(SLIP)model has been extensively employed in both biomechanical study and robotics research.Aiming at fully leveraging the merits of the SLIP model to generate the adaptive trajectories of the center of mass(CoM)with maneuverability,this study presents a novel two-layered sagittal SLIP-anchored(SSA)task space control for a monopode robot to deal with terrain irregularity.This work begins with an analytical investigation of sagittal SLIP dynamics by deriving an approximate solution with satisfactory apex prediction accuracy,and a two-layered SSA task space controller is subsequently developed for the monopode robot.The higher layer employs an analytical approximate representation of the sagittal SLIP model to form a deadbeat controller,which generates an adaptive reference trajectory for the CoM.The lower layer enforces the monopode robot to reproduce a generated CoM movement by using a task space controller to transfer the reference CoM commands into joint torques of the multi-degree of freedom monopode robot.Consequently,an adaptive hopping behavior is exhibited by the robot when traversing irregular terrain.Simulation results have demonstrated the effectiveness of the proposed method.展开更多
Aimed at capture task for a free-floating space manipulator, a scheme of pre-impact trajectory planning for minimizing base attitude disturbance caused by impact is proposed in this paper.Firstly, base attitude distur...Aimed at capture task for a free-floating space manipulator, a scheme of pre-impact trajectory planning for minimizing base attitude disturbance caused by impact is proposed in this paper.Firstly, base attitude disturbance is established as a function of joint angles, collision direction and relative velocity between robotic hand and the target.Secondly, on the premise of keeping correct capture pose, a novel optimization factor in null space is designed to minimize base attitude disturbance and ensure that the joint angles do not exceed their limits simultaneously.After reaching the balance state, a desired configuration is achieved at the contact point.Thereafter, particle swarm optimization（PSO） algorithm is employed to solve the pre-impact trajectory planning from its initial configuration to the desired configuration to achieve the minimized base attitude disturbance caused by impact and the correct capture pose simultaneously.Finally, the proposed method is applied to a 7-dof free-floating space manipulator and the simulation results verify the effectiveness.展开更多
A free-flying space robot will accomplish manufacturing, assembling and repair instead of astronauts in the future unmanned space flight hbecause of its flexible maneuverability in space. This paper presents a task pl...A free-flying space robot will accomplish manufacturing, assembling and repair instead of astronauts in the future unmanned space flight hbecause of its flexible maneuverability in space. This paper presents a task planning algorithm of retrieving invalid satellite for free-fiving space robot. First we discuss kinematics model and deduct cinematics equations of dual-arm space robot. Then the process of retrieving an invalid satellite, which is divided into eleven motion procedures. At the same time, we have developed a free-flying space robot task planning simulation system and the experimental results show that this algorithm is feasible and correct.展开更多
This paper presents a novel hybrid task priority-based motion planning algorithm of a space robot. The satellite attitude control task is defined as the primary task, while the leastsquares-based non-strict task prior...This paper presents a novel hybrid task priority-based motion planning algorithm of a space robot. The satellite attitude control task is defined as the primary task, while the leastsquares-based non-strict task priority solution of the end-effector plus the multi-constraint task is viewed as the secondary task. Furthermore, a null-space task compensation strategy in the joint space is proposed to derive the combination of non-strict and strict task-priority motion planning,and this novel combination is termed hybrid task priority control. Thus, the secondary task is implemented in the primary task＇s null-space. Besides, the transition of the state of multiple constraints between activeness and inactiveness will only influence the end-effector task without any effect on the primary task. A set of numerical experiments made in a real-time simulation system under Linux/RTAI shows the validity and feasibility of the proposed methodology.展开更多
空天地融合车载网场景下,无人机设备由于电池容量和能源有限,无法为任务卸载提供长期有效支持;低轨卫星受资源成本以及通信延迟、时延抖动的影响难以为大规模车联网任务提供稳定的高带宽通信服务。针对空天地融合车载网络场景下无人机...空天地融合车载网场景下,无人机设备由于电池容量和能源有限,无法为任务卸载提供长期有效支持;低轨卫星受资源成本以及通信延迟、时延抖动的影响难以为大规模车联网任务提供稳定的高带宽通信服务。针对空天地融合车载网络场景下无人机和低轨卫星的资源优化问题,提出了一种基于多任务深度强化辅助学习(Multi-Task Deep Reinforcement and Auxiliary Learning,MTDRAL)的任务卸载以及功率调整、缓存决策的方案。首先构建了任务切分与传输模型、时延模型、能耗模型、服务器计算与缓存模型和问题模型;然后,基于对任务处理时延、服务器能耗以及缓存命中率的综合考虑,给出了基于MTDRAL的任务卸载及资源调度方案;最后将所提方案与随机卸载策略方案、成功率贪婪决策方案、基于柔性动作-评价算法的多网络深度强化学习的卸载方案、基于深度确定性策略梯度算法的多网络深度强化学习的卸载方案进行了对比实验。实验结果表明:所提方案在服务器数量为14、车载终端数量为10时,综合得分相较于4种对比方案,分别领先约134.41%,31.32%,38.93%,29.49%;所提方案具有较好的性能,能更好地满足空天地融合车载网场景下的任务卸载需求。展开更多
基金supported by the National Basic Research Program of China (973 Program) (No.2009CB320601)National Natural Science Foundationof China (No.60534010)+1 种基金the Funds for Creative Research Groups of China (No.60521003)the 111 Project (No.B08015)
文摘A neural-network-based motion controller in task space is presented in this paper.The proposed controller is addressed as a two-loop cascade control scheme.The outer loop is given by kinematic control in the task space.It provides a joint velocity reference signal to the inner one.The inner loop implements a velocity servo loop at the robot joint level.A radial basis function network(RBFN)is integrated with proportional-integral(PI)control to construct a velocity tracking control scheme for the inner loop.Finally,a prototype technology based control system is designed for a robotic manipulator.The proposed control scheme is applied to the robotic manipulator.Experimental results confirm the validity of the proposed control scheme by comparing it with other control strategies.
文摘Trajectory tracking control of space robots in task space is of great importance to space missions, which require on-orbit manipulations. This paper focuses on position and attitude tracking control of a tree-floating space robot in task space. Since nei- ther the nonlinear terms and parametric uncertainties of the dynamic model, nor the external disturbances are known, an adap- tive radial basis function network based nonsingular terminal sliding mode （RBF-NTSM） control method is presented. The proposed algorithm combines the nonlinear sliding manifold with the radial basis function to improve control performance. Moreover, in order to account for actuator physical constraints, a constrained adaptive RBF-NTSM, which employs a RBF network to compensate for the limited input is developed. The adaptive updating laws acquired by Lyapunov approach guar- antee the global stability of the control system and suppress chattering problems. Two examples are provided using a six-link free-floating space robot. Simulation results clearly demonstrate that the proposed constrained adaptive RBF-NTSM control method performs high precision task based on incomplete dynamic model of the space robots. In addition, the control errors converge faster and the chattering is eliminated comparing to traditional sliding mode control.
基金the National Natural Science Foundation of China (No. 60305008)
文摘This paper deals with a flexible macro-micro manipulator system, which includes a long flexible manipulator and a relatively short rigid manipulator attached to the tip of the macro manipulator. A flexible macro manipulator possesses the advantages of wide operating range, high speed, and low energy consumption, but the disadvantage of a low tracking precision. The macro-micro manipulator system improves tracking performance by compensating for the endpoint tracking error while maintaining the advantages of the flexible macro manipulator. A trajectory planning scheme was built utilizing the task space division method. The division point is chosen to optimize the error compensation and energy consumption for the whole system. Then movements of the macro-micro manipulator can be determined using separate inverse kinematic models. Simulation results for a planar 4-DOF macro-micro manipulator system are presented to show the effectiveness of the control system.
基金This work was supported by the National Natural Science Foundation of China(Grant No.51605115)State Key Laboratory of Robotics and System(Self-Planned Task No.SKLRS201719A)+1 种基金Heilongjiang Postdoctoral Financial Assistance(Grant No.LBH-Z16083)Natural Science Foundation of Heilongjiang Province(Grant No.QC2017052).
文摘As a well-explored template that captures the essential dynamical behaviors of legged locomotion on sagittal plane,the spring-loaded inverted pendulum(SLIP)model has been extensively employed in both biomechanical study and robotics research.Aiming at fully leveraging the merits of the SLIP model to generate the adaptive trajectories of the center of mass(CoM)with maneuverability,this study presents a novel two-layered sagittal SLIP-anchored(SSA)task space control for a monopode robot to deal with terrain irregularity.This work begins with an analytical investigation of sagittal SLIP dynamics by deriving an approximate solution with satisfactory apex prediction accuracy,and a two-layered SSA task space controller is subsequently developed for the monopode robot.The higher layer employs an analytical approximate representation of the sagittal SLIP model to form a deadbeat controller,which generates an adaptive reference trajectory for the CoM.The lower layer enforces the monopode robot to reproduce a generated CoM movement by using a task space controller to transfer the reference CoM commands into joint torques of the multi-degree of freedom monopode robot.Consequently,an adaptive hopping behavior is exhibited by the robot when traversing irregular terrain.Simulation results have demonstrated the effectiveness of the proposed method.
基金supported by the National Basic Research Program of China (No.2013CB733000)the National Natural Science Foundation of China (No.61175080)BUPT Excellent Ph.D.Students Foundation of China (No.CX201427)
文摘Aimed at capture task for a free-floating space manipulator, a scheme of pre-impact trajectory planning for minimizing base attitude disturbance caused by impact is proposed in this paper.Firstly, base attitude disturbance is established as a function of joint angles, collision direction and relative velocity between robotic hand and the target.Secondly, on the premise of keeping correct capture pose, a novel optimization factor in null space is designed to minimize base attitude disturbance and ensure that the joint angles do not exceed their limits simultaneously.After reaching the balance state, a desired configuration is achieved at the contact point.Thereafter, particle swarm optimization（PSO） algorithm is employed to solve the pre-impact trajectory planning from its initial configuration to the desired configuration to achieve the minimized base attitude disturbance caused by impact and the correct capture pose simultaneously.Finally, the proposed method is applied to a 7-dof free-floating space manipulator and the simulation results verify the effectiveness.
文摘A free-flying space robot will accomplish manufacturing, assembling and repair instead of astronauts in the future unmanned space flight hbecause of its flexible maneuverability in space. This paper presents a task planning algorithm of retrieving invalid satellite for free-fiving space robot. First we discuss kinematics model and deduct cinematics equations of dual-arm space robot. Then the process of retrieving an invalid satellite, which is divided into eleven motion procedures. At the same time, we have developed a free-flying space robot task planning simulation system and the experimental results show that this algorithm is feasible and correct.
基金supported in part by the National Program on Key Basic Research Project (No. 2013CB733103)the Program for New Century Excellent Talents in University (No. NCET-10-0058)
文摘This paper presents a novel hybrid task priority-based motion planning algorithm of a space robot. The satellite attitude control task is defined as the primary task, while the leastsquares-based non-strict task priority solution of the end-effector plus the multi-constraint task is viewed as the secondary task. Furthermore, a null-space task compensation strategy in the joint space is proposed to derive the combination of non-strict and strict task-priority motion planning,and this novel combination is termed hybrid task priority control. Thus, the secondary task is implemented in the primary task＇s null-space. Besides, the transition of the state of multiple constraints between activeness and inactiveness will only influence the end-effector task without any effect on the primary task. A set of numerical experiments made in a real-time simulation system under Linux/RTAI shows the validity and feasibility of the proposed methodology.
文摘空天地融合车载网场景下,无人机设备由于电池容量和能源有限,无法为任务卸载提供长期有效支持;低轨卫星受资源成本以及通信延迟、时延抖动的影响难以为大规模车联网任务提供稳定的高带宽通信服务。针对空天地融合车载网络场景下无人机和低轨卫星的资源优化问题,提出了一种基于多任务深度强化辅助学习(Multi-Task Deep Reinforcement and Auxiliary Learning,MTDRAL)的任务卸载以及功率调整、缓存决策的方案。首先构建了任务切分与传输模型、时延模型、能耗模型、服务器计算与缓存模型和问题模型;然后,基于对任务处理时延、服务器能耗以及缓存命中率的综合考虑,给出了基于MTDRAL的任务卸载及资源调度方案;最后将所提方案与随机卸载策略方案、成功率贪婪决策方案、基于柔性动作-评价算法的多网络深度强化学习的卸载方案、基于深度确定性策略梯度算法的多网络深度强化学习的卸载方案进行了对比实验。实验结果表明:所提方案在服务器数量为14、车载终端数量为10时,综合得分相较于4种对比方案,分别领先约134.41%,31.32%,38.93%,29.49%;所提方案具有较好的性能,能更好地满足空天地融合车载网场景下的任务卸载需求。
