A kinematically redundant robot, with more degrees of freedom than re-quired to complete a desired task, can be usefu1 because of its inherent kinematics flexibili-ty and dynamic performance. lt is very difficu1t, how...A kinematically redundant robot, with more degrees of freedom than re-quired to complete a desired task, can be usefu1 because of its inherent kinematics flexibili-ty and dynamic performance. lt is very difficu1t, however, to implement optimal redun-dancy control, while simultaneously taking into account hath kinematics and dynamics.To realize dua1-optimization control, a new redundant robot mechanism with local degreesof freedom is introduced, and its kinematics and dynamics features are investigated. Simu-lation results demonstrate the effectiveness of the proPosed method.展开更多
The kinematic redundancy in a robot leads to an infinite number of solutions for inverse kinematics, which implies the possibility to select a 'best' solution according to an optimization criterion. In this pa...The kinematic redundancy in a robot leads to an infinite number of solutions for inverse kinematics, which implies the possibility to select a 'best' solution according to an optimization criterion. In this paper, two optimization objective functions are proposed, aiming at either minimizing extra degrees of freedom (DOFs) or minimizing the total potential energy of a multilink redundant robot. Physical constraints of either equality or inequality types are taken into consideration in the objective functions. Since the closed-form solutions do not exist in general for highly nonlinear and constrained optimization problems, we adopt and develop two numerical methods, which are verified to be effective and precise in solving the two optimization problems associated with the redundant inverse kinematics. We first verify that the well established trajectory following method can precisely solve the two optimization problems, but is computation intensive. To reduce the computation time, a sequential approach that combines the sequential quadratic programming and iterative Newton-Raphson algorithm is developed. A 4-DOF Fujitsu Hoap-1 humanoid robot arm is used as a prototype to validate the effectiveness of the proposed optimization solutions.展开更多
Multibody system dynamics provides a strong tool for the estimation of dynamic performances and the optimization of multisystem robot design. It can be described with differential algebraic equations(DAEs). In this pa...Multibody system dynamics provides a strong tool for the estimation of dynamic performances and the optimization of multisystem robot design. It can be described with differential algebraic equations(DAEs). In this paper, a particle swarm optimization(PSO) method is introduced to solve and control a symplectic multibody system for the first time. It is first combined with the symplectic method to solve problems in uncontrolled and controlled robotic arm systems. It is shown that the results conserve the energy and keep the constraints of the chaotic motion, which demonstrates the efficiency, accuracy, and time-saving ability of the method. To make the system move along the pre-planned path, which is a functional extremum problem, a double-PSO-based instantaneous optimal control is introduced. Examples are performed to test the effectiveness of the double-PSO-based instantaneous optimal control. The results show that the method has high accuracy, a fast convergence speed, and a wide range of applications.All the above verify the immense potential applications of the PSO method in multibody system dynamics.展开更多
Cable-driven parallel robot(CDPR)is a type of high-performance robot that integrates cable-driven kinematic chains and parallel mechanism theory.It inherits the high dynamics and heavy load capacities of the parallel ...Cable-driven parallel robot(CDPR)is a type of high-performance robot that integrates cable-driven kinematic chains and parallel mechanism theory.It inherits the high dynamics and heavy load capacities of the parallel mechanism and significantly improves the workspace,cost and energy efficiency simultaneously.As a result,CDPRs have had irreplaceable roles in industrial and technological fields,such as astronomy,aerospace,logistics,simulators,and rehabilitation.CDPRs follow the cutting-edge trend of rigid-flexible fusion,reflect advanced lightweight design concepts,and have become a frontier topic in robotics research.This paper summarizes the kernel theories and developments of CDPRs,covering configuration design,cable-force distribution,workspace and stiffness,performance evaluation,optimization,and motion control.Kinematic modeling,workspace analysis,and cable-force solution are illustrated.Stiffness and dynamic modeling methods are discussed.To further promote the development,researchers should strengthen the investigation in configuration innovation,rapid calculation of workspace,performance evaluation,stiffness control,and rigid-flexible coupling dynamics.In addition,engineering problems such as cable materials,reliability design,and a unified control framework require attention.展开更多
A certain number of considerations should be taken into account in the dynamic control of robot manipulators as highly complex non-linear systems.In this article,we provide a detailed presentation of the mechanical an...A certain number of considerations should be taken into account in the dynamic control of robot manipulators as highly complex non-linear systems.In this article,we provide a detailed presentation of the mechanical and electrical impli- cations of robots equipped with DC motor actuators.This model takes into account all non-linear aspects of the system.Then,we develop computational algorithms for optimal control based on dynamic programming.The robot's trajectory must be predefined,but performance criteria and constraints applying to the system are not limited and we may adapt them freely to the robot and the task being studied.As an example,a manipulator arm with 3 degrees of freedom is analyzed.展开更多
针对传统快速随机搜索树*(rapidly-exploring random tree*,RRT*)算法收敛速率较慢,且不适用于动态场景等问题,提出一种基于目标点偏置和冗余节点删除的改进RRT*算法,用于解决移动机器人快速找到无碰撞最优路径的问题。此算法在RRT*算...针对传统快速随机搜索树*(rapidly-exploring random tree*,RRT*)算法收敛速率较慢,且不适用于动态场景等问题,提出一种基于目标点偏置和冗余节点删除的改进RRT*算法,用于解决移动机器人快速找到无碰撞最优路径的问题。此算法在RRT*算法基础上,首先对采样点进行优化处理,保证路径最优的同时减少搜寻时间;其次引入路径节点最大值概念,删除扩展树冗余节点以提高算法效率;最后结合动态窗口(dynamic window approaches,DWA)算法提高路径的安全性和平滑性,实现对动态障碍物的避障。通过3种不同地图下的仿真验证,改进算法能有效提升路径质量,且大幅降低运行时间。展开更多
To raise the optimizing ability of the redundant manipulators, a modified weighted gradient projection method(MWGPM) to optimize kinematics is presented.Two new concepts, the matrix weightability measure(MWM) and the ...To raise the optimizing ability of the redundant manipulators, a modified weighted gradient projection method(MWGPM) to optimize kinematics is presented.Two new concepts, the matrix weightability measure(MWM) and the self-motion declinability measure(SMDM) are proposed. Thus the weighting ability of the weighting matrix and the self-motion amplitude decided by the homogeneous solution could be continuously regulated. MWGPM has the merits which belong to both the least-norm solution (WLN), and gradient projection method(GPM), and it can obtain ideal optimizing effects at low joint velocities, which has been verified by simulation.展开更多
文摘A kinematically redundant robot, with more degrees of freedom than re-quired to complete a desired task, can be usefu1 because of its inherent kinematics flexibili-ty and dynamic performance. lt is very difficu1t, however, to implement optimal redun-dancy control, while simultaneously taking into account hath kinematics and dynamics.To realize dua1-optimization control, a new redundant robot mechanism with local degreesof freedom is introduced, and its kinematics and dynamics features are investigated. Simu-lation results demonstrate the effectiveness of the proPosed method.
文摘The kinematic redundancy in a robot leads to an infinite number of solutions for inverse kinematics, which implies the possibility to select a 'best' solution according to an optimization criterion. In this paper, two optimization objective functions are proposed, aiming at either minimizing extra degrees of freedom (DOFs) or minimizing the total potential energy of a multilink redundant robot. Physical constraints of either equality or inequality types are taken into consideration in the objective functions. Since the closed-form solutions do not exist in general for highly nonlinear and constrained optimization problems, we adopt and develop two numerical methods, which are verified to be effective and precise in solving the two optimization problems associated with the redundant inverse kinematics. We first verify that the well established trajectory following method can precisely solve the two optimization problems, but is computation intensive. To reduce the computation time, a sequential approach that combines the sequential quadratic programming and iterative Newton-Raphson algorithm is developed. A 4-DOF Fujitsu Hoap-1 humanoid robot arm is used as a prototype to validate the effectiveness of the proposed optimization solutions.
基金Project supported by the National Natural Science Foundation of China(Nos.91648101 and11672233)the Northwestern Polytechnical University(NPU)Foundation for Fundamental Research(No.3102017AX008)the National Training Program of Innovation and Entrepreneurship for Undergraduates(No.S201710699033)
文摘Multibody system dynamics provides a strong tool for the estimation of dynamic performances and the optimization of multisystem robot design. It can be described with differential algebraic equations(DAEs). In this paper, a particle swarm optimization(PSO) method is introduced to solve and control a symplectic multibody system for the first time. It is first combined with the symplectic method to solve problems in uncontrolled and controlled robotic arm systems. It is shown that the results conserve the energy and keep the constraints of the chaotic motion, which demonstrates the efficiency, accuracy, and time-saving ability of the method. To make the system move along the pre-planned path, which is a functional extremum problem, a double-PSO-based instantaneous optimal control is introduced. Examples are performed to test the effectiveness of the double-PSO-based instantaneous optimal control. The results show that the method has high accuracy, a fast convergence speed, and a wide range of applications.All the above verify the immense potential applications of the PSO method in multibody system dynamics.
基金This work was supported in part by the National Natural Science Foundation of China(Grant Nos.52105025 and U19A20101).
文摘Cable-driven parallel robot(CDPR)is a type of high-performance robot that integrates cable-driven kinematic chains and parallel mechanism theory.It inherits the high dynamics and heavy load capacities of the parallel mechanism and significantly improves the workspace,cost and energy efficiency simultaneously.As a result,CDPRs have had irreplaceable roles in industrial and technological fields,such as astronomy,aerospace,logistics,simulators,and rehabilitation.CDPRs follow the cutting-edge trend of rigid-flexible fusion,reflect advanced lightweight design concepts,and have become a frontier topic in robotics research.This paper summarizes the kernel theories and developments of CDPRs,covering configuration design,cable-force distribution,workspace and stiffness,performance evaluation,optimization,and motion control.Kinematic modeling,workspace analysis,and cable-force solution are illustrated.Stiffness and dynamic modeling methods are discussed.To further promote the development,researchers should strengthen the investigation in configuration innovation,rapid calculation of workspace,performance evaluation,stiffness control,and rigid-flexible coupling dynamics.In addition,engineering problems such as cable materials,reliability design,and a unified control framework require attention.
文摘A certain number of considerations should be taken into account in the dynamic control of robot manipulators as highly complex non-linear systems.In this article,we provide a detailed presentation of the mechanical and electrical impli- cations of robots equipped with DC motor actuators.This model takes into account all non-linear aspects of the system.Then,we develop computational algorithms for optimal control based on dynamic programming.The robot's trajectory must be predefined,but performance criteria and constraints applying to the system are not limited and we may adapt them freely to the robot and the task being studied.As an example,a manipulator arm with 3 degrees of freedom is analyzed.
文摘针对传统快速随机搜索树*(rapidly-exploring random tree*,RRT*)算法收敛速率较慢,且不适用于动态场景等问题,提出一种基于目标点偏置和冗余节点删除的改进RRT*算法,用于解决移动机器人快速找到无碰撞最优路径的问题。此算法在RRT*算法基础上,首先对采样点进行优化处理,保证路径最优的同时减少搜寻时间;其次引入路径节点最大值概念,删除扩展树冗余节点以提高算法效率;最后结合动态窗口(dynamic window approaches,DWA)算法提高路径的安全性和平滑性,实现对动态障碍物的避障。通过3种不同地图下的仿真验证,改进算法能有效提升路径质量,且大幅降低运行时间。
文摘To raise the optimizing ability of the redundant manipulators, a modified weighted gradient projection method(MWGPM) to optimize kinematics is presented.Two new concepts, the matrix weightability measure(MWM) and the self-motion declinability measure(SMDM) are proposed. Thus the weighting ability of the weighting matrix and the self-motion amplitude decided by the homogeneous solution could be continuously regulated. MWGPM has the merits which belong to both the least-norm solution (WLN), and gradient projection method(GPM), and it can obtain ideal optimizing effects at low joint velocities, which has been verified by simulation.
文摘针对工厂化蘑菇种植中人工采摘费时、费力等问题,研制了一款蘑菇采摘机器人.首先,采用模块化设计了采摘机器人机械结构,基于D-H法推导机器人运动学正解和逆解,并进一步分析了采摘手臂的动力学性能;以采摘效率为目标建立了手臂尺寸的多目标优化模型,并用遗传算法求最优解;然后建立Adams虚拟样机模型,对优化前后的机器人模型分别进行采摘动力学仿真试验,结果表明,在电动机输出转矩相同情况下,大臂关节和小臂关节最大角速度分别提高22.9%和18.6%,单次采摘时间由1.60 s缩短到1.36 s,速度提高15%;最后研制原理样机并进行采摘试验,试验结果表明,所研制的机器人可适用于工厂化蘑菇种植模式下多层菇床中狭小、大面积作业的自动化采摘,单次蘑菇采摘时间约为2.0 s.
