Neural Dynamics for Cooperative Motion Control of Omnidirectional Mobile Manipulators in the Presence of Noises: A Distributed Approach

This paper presents a distributed scheme with limited communications, aiming to achieve cooperative motion control for multiple omnidirectional mobile manipulators(MOMMs).The proposed scheme extends the existing single-agent motion control to cater to scenarios involving the cooperative operation of MOMMs. Specifically, squeeze-free cooperative load transportation is achieved for the end-effectors of MOMMs by incorporating cooperative repetitive motion planning(CRMP), while guiding each individual to desired poses. Then, the distributed scheme is formulated as a time-varying quadratic programming(QP) and solved online utilizing a noise-tolerant zeroing neural network(NTZNN). Theoretical analysis shows that the NTZNN model converges globally to the optimal solution of QP in the presence of noise. Finally, the effectiveness of the control design is demonstrated by numerical simulations and physical platform experiments.

Kinematic Analysis of Mobile Manipulator for Measurement and Maintenance in Dangerous Environment

This paper studies the kinematic modeling of a mobile manipulator that consists of 5-DOF manipulator and an autonomous wheeled mobile platform.Then an artificial neural network to realize the coordination motion between manipulator and mobile platform is developed.On the basis of the task specifications,the algorithm determines the appropriate control variables to respond to the well tracking trajectory.The control strategy employed for either subsystem is achieved by using a robust supervised controller.A learning paradigm is used to produce the required reference variables for an overall cooperative behavior of the sys- tem.Simulation results are presented to show the effectiveness of this approach.

Robust Adaptive Control for Mobile Manipulators

This paper addresses the trajectory tracking control of a nonholonomic wheeled mobile manipulator with parameter uncertainties and disturbances. The proposed algorithm adopts a robust adaptive control strategy where parametric uncertainties are compensated by adaptive update techniques and the disturbances are suppressed. A kinematic controller is first designed to make the robot follow a desired end-effector and platform trajectories in task space coordinates simultaneously. Then, an adaptive control scheme is proposed, which ensures that the trajectories are accurately tracked even in the presence of external disturbances and uncertainties. The system stability and the convergence of tracking errors to zero are rigorously proven using Lyapunov theory. Simulations results are given to illustrate the effectiveness of the proposed robust adaptive control law in comparison with a sliding mode controller.

Implementation and Kinematic Control of a Hyper-redundant Mobile Manipulator System

Redundant or hyper-redundant mobile manipulator can give lots of assistance to astronauts in space station. The design and implementation of a hyper-redundant mobile manipulator system are described, which is composed of an 8 DOF module robot and a 1 DOF motorized rail. Inverse kinematic resolution of the system is discussed and one simplified control method based on joint limit avoidance and configuration optimization is proposed. Simulation and experimental results are presented.

Control of a 6DOF Mobile Manipulator with Object Detection and Tracking Using Stereo Vision

A supportive mobile robot for assisting the elderly is an emerging requirement mainly in countries like Japan where population ageing become relevant in near future.Falls related injuries are considered as a critical issue when taking into account the physical health of older people.A personal assistive robot with the capability of picking up and carrying objects for long/short distances can be used to overcome or lessen this problem.Here,we design and introduce a 3 D dynamic simulation of such an assistive robot to perform pick and place of objects through visual recognition.The robot consists of two major components;a robotic arm or manipulator to do the pick and place,and an omnidirectional wheeled robotic platform to support mobility.Both components are designed and operated according to their kinematics and dynamics and the controllers are integrated for the combined performance.The objective was to improve the accuracy of the robot at a considerably high speed.Designed mobile manipulator has been successfully tested and simulated with a stereo vision system to perform object recognition and tracking in a virtual environment resembling aroom of an elderly care.The tracking accuracy of the mobile manipulator at an average speed of 0.5 m/s is 90%and is well suited for the proposed application.

Dexterity Analysis for Omni-directional Wheeled Mobile Manipulator Based on Double Quaternion

The unified analysis of omni-directional wheeled mobile manipulator(OWMM) through the dimensionally nonhomogeneous Jacobian matrix may lead to unreliable results. The existing researches focus on the integrated performance evaluation of OWMM, without taking the influence of velocity difference into consideration. This paper presents a new approach to formulate the dimensionally homogeneous Jacobian matrix and a new index for OWMM. First, the universal transformational matrix of the link coordinate frame is derived based on double quaternion. The degree of locomotion of a mobile platform and the degrees of manipulation of a manipulator are treated equally as the joints of a redundant composite robot. Then the integrated modeling of OWMM is established, and the non-dimensional Jacobian matrix is obtained from the above matrix. Next, by examining the concept of directional manipulability, a new index is proposed to evaluate the directional manipulability of OWMM along the specified task direction. Furthermore, for the same task and the time of simulation, the kinematic performance of the fixed base operation of the manipulator and the operation of OWMM are analyzed by numerical simulation. The results suggest that the proposed approach is equivalent to the method of traditional kinematic modeling, with the error of numerical solution being 10-7 , and the varying frequency of DMTR is higher than that of the condition number. This indicates that DMTR is more effective to reflect the variation of the task direction. The proposed method can be used to analyze the manipulating capability of OWMM, and has a simple structure and generality in the unified analysis of OWMM.

Trajectory planning of mobile manipulators in constrained workspace

The cooperative motion planning of nonholonomic wheeled mobile manipulators （WMM） with kinematic redundaney in the constrained workspace was studied. A trajectory planning method combining the probabilistic planning and the solving of inverse kinematic equations was presented. First, the probabilistie planning method was used to determine the guide configurations; then the switching objective function was defined and the path of the end-effector was constructed based on these guide configurations ; finally, the inverse kinematic equations of the WMM were solved using the gradient projection method, and the obstacle avoidance trajectory for joints of the WMM was obtained. Simulation results were given to demonstrate the effectiveness of the proposed method.

Self-motion Manifolds of an 8-DOF Non-holonomic Mobile Manipulator

For the non-holonomic constraint robot,determining the pose of its end-effector will rely on its joints' displacement and the velocity of its non-holonomic constraint joints as well.Therefore,it becomes increasingly difficult to obtain the analytic solution of its self-motion manifold in the traditional way for solving matrix equation.In this paper,we take the pose of end manipulator as the result of the joint sequential motion based on the mentality of motion equivalence,the structure and the reference velocity which correspond precisely to the points in self-motion manifold as self-motion variable.Thus an analytical solution for the self-motion manifold of the 8 degree of freedom wheeled mobile manipulator is presented by taking vector algebra as a tool,which facilitates deriving the closed solution of its self-motion manifold.In the closing part of this paper,calculating examples of self-motion manifold and mechanism self-motion simulation are proposed,which proves the validity of solution algorithm for self-motion manifold.

Multiple mobile-obstacle avoidance algorithm for redundant manipulator

In order to overcome the shortcomings of the previous obstacle avoidance algorithms,an obstacle avoidance algorithm applicable to multiple mobile obstacles was proposed.The minimum prediction distance between obstacles and a manipulator was obtained according to the states of obstacles and transformed to escape velocity of the corresponding link of the manipulator.The escape velocity was introduced to the gradient projection method to obtain the joint velocity of the manipulator so as to complete the obstacle avoidance trajectory planning.A7-DOF manipulator was used in the simulation,and the results verified the effectiveness of the algorithm.

Locomotion Optimization and Manipulation Planning of a Tetrahedron-Based Mobile Mechanism with Binary Control

Locomotion and manipulation optimization is essential for the performance of tetrahedron-based mobile mechanism. Most of current optimization methods are constrained to the continuous actuated system with limited degree of freedom(DOF), which is infeasible to the optimization of binary control multi-DOF system. A novel optimization method using for the locomotion and manipulation of an 18 DOFs tetrahedron-based mechanism called 5-TET is proposed. The optimization objective is to realize the required locomotion by executing the least number of struts.Binary control strategy is adopted, and forward kinematic and tipping dynamic analyses are performed, respectively.Based on a developed genetic algorithm(GA), the optimal number of alternative struts between two adjacent steps is obtained as 5. Finally, a potential manipulation function is proposed, and the energy consumption comparison between optimal 5-TET and the traditional wheeled robot is carried out. The presented locomotion optimization and manipulation planning enrich the research of tetrahedron-based mechanisms and provide the instruction to the successive locomotion and operation planning of multi-DOF mechanisms.

An Adaptive Fuzzy Control Model for Multi-Joint Manipulators

Multi-joint manipulator systems are subject to nonlinear influences such as frictional characteristics,random disturbances and load variations.To account for uncertain disturbances in the operation of manipulators,we propose an adaptive manipulator control method based on a multi-joint fuzzy system,in which the upper bound information of the fuzzy system is constant and the state variables of the manipulator control system are measurable.The control algorithm of the system is a MIMO(multi-input-multi-output)fuzzy system that can approximate system error by using a robust adaptive control law to eliminate the shadow caused by approximation error.It can ensure the stability of complex manipulator control systems and reduce the number of fuzzy rules required.Comparison of experimental and simulation data shows that the controller designed using this algorithm has highly-precise trajectory-tracking control and can control robotic systems with complex characteristics of non-linearity,coupling and uncertainty.Therefore,the proposed algorithm has good practical application prospects and promotes the development of complex control systems.

IHMP:an improved hierarchical motion planner for mobile manipulator in static environment

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.

Base position planning of mobile manipulators for assembly tasks in construction environments

With good mobility and flexibility,mobile manipulators have shown broad applications in construction scenarios.Base position(BP)planning,which refers to the robot autonomously determining its working station in the environment,is an important technique for mobile manipulators when performing the construction assembly task,especially in a large-scale construction environment.However,the BP planning process is tedious and time-consuming for a human worker to carry out.Thus,to improve the efficiency of construction assembly tasks,a novel BP planning method is proposed in this paper,which can lead to appropriate BPs and minimize the number of BPs at the same time.Firstly,the feasible BP regions are generated based on the grid division and the variable workspace of the mobile manipulator.Then,the positioning uncertainties of the mobile manipulator are considered in calculating the preferred BP areas using clustering.Lastly,a set coverage optimization model is established to obtain the minimum number of BPs using an optimization algorithm according to the greedy principle.The simulated experiment based on a 9-degree of free(DoF)mobile manipulator has been performed.The results illustrated that the time for BP planning was significantly reduced and the number of BPs was reduced by 63.41%compared to existing manual planning,which demonstrated the effectiveness of the proposed method.

Input-Constrained Hybrid Control of a Hyper-Redundant Mobile Medical Manipulator

To reduce the risk of infection in medical personnel working in infectious-disease areas, we proposed ahyper-redundant mobile medical manipulator (HRMMM) to perform contact tasks in place of healthcare workers.A kinematics-based tracking algorithm was designed to obtain highly accurate pose tracking. A kinematic modelof the HRMMM was established and its global Jacobian matrix was deduced. An expression of the trackingerror based on the Rodrigues rotation formula was designed, and the relationship between tracking errors andgripper velocities was derived to ensure accurate object tracking. Considering the input constraints of the physicalsystem, a joint-constraint model of the HRMMM was established, and the variable-substitution method was usedto transform asymmetric constraints to symmetric constraints. All constraints were normalized by dividing bytheir maximum values. A hybrid controller based on pseudo-inverse (PI) and quadratic programming (QP) wasdesigned to satisfy the real-time motion-control requirements in medical events. The PI method was used whenthere was no input saturation, and the QP method was used when saturation occurred. A quadratic performanceindex was designed to ensure smooth switching between PI and QP. The simulation results showed that theHRMMM could approach the target pose with a smooth motion trajectory, while meeting different types of inputconstraints.

一种全向移动操作机器人建模与交互作用分析

全向移动操作机器人(Omni-directional Mobile Manipulating Robots,OMMR)是由全向移动平台以及在平台上加装一个或多个操作臂组成的具有主动作业能力的新型机器人系统。在移动平台上加装操作臂后,整个系统动力学行为的复杂性将会因为移动平台与操作臂之间的耦合效应而大大增加,涉及地面-移动平台、移动平台-操作臂、操作臂-操作环境的动态交互,给系统的建模带来极大困难。在建立OMMR运动学、静力学模型的基础上,提出了一种简化的OMMR系统动力学建模方法;基于该动力学模型,建立车-臂交互作用模型并对其交互作用进行分析。仿真和实验验证了车-臂交互作用模型的正确性,间接证明了所提OMMR系统动力学建模方法的合理性和有效性,为机器人运动规划和运动控制提供了模型数据。

基于CODESYS平台的移动机械臂运动控制系统设计

针对传统六关节机械臂操作空间有限的问题,以移动底盘和Elfin05机械臂为控制对象,采用ARM+CODESYS架构和PLCopen规范设计了一款移动机械臂运动控制器。首先根据MD-H参数与坐标变换思想建立移动机械臂正运动学模型,基于关节角参数化解析法简化移动机械臂的冗余度进行逆运动学求解,并设计相应运动学功能块;其次采用分布式控制思想设计控制模块,以SM3_CNC库为基础设计了机械臂的点到点运动控制功能块,基于Backstepping法设计了移动底盘的跟踪控制功能块;再次以Visualization模块为基础设计人机交互界面;最后以该机器人为实验对象进行实验,实现了移动底盘与机械臂的协同运动,增加了传统六关节机械臂可操作空间,并验证了该运动控制器设计的有效性。

基于改进A*算法和可操作度的移动机械臂运动规划研究

针对移动机械臂在室内环境下规划时间长、取放运动可操作性差等问题,提出了改进常规A*算法,以机械臂可操作度值作为评价标准,确定最佳停靠位置并进行系统运动规划的方法。首先,在常规A*算法的基础上,将8个搜索方向简化为5个,以提高搜索效率;同时,设计了一种新的启发式搜索函数,将Floyd算法引入到A*算法中,增加路径的平滑度。仿真结果显示,改进后的A*算法相比常规A*算法运行时间缩短59.1%,路径长度减少3.5%,搜索节点数减少41.6%。其次,根据机械臂的可达工作空间与雅可比矩阵,评估移动机械臂在待取放目标物体附近不同位置下的可操作度值,优化停靠位置,从而提高取放运动的可操作性。最后,采用由DIY机械臂和Turtlebot2移动机器人组成的移动机械臂系统,在室内环境中完成了运动规划综合实验,验证了所提方法的有效性和可靠性。

基于具身智能的移动操作机器人系统发展研究

具身智能是新一轮科技革命与产业变革中的战略性技术,是当前世界各国重点竞争的前沿高地之一;移动操作机器人系统因其优秀的运动、规划、执行能力成为具身技术首选的硬件载体;基于具身智能的移动操作机器人系统作为实现跨领域、多场景、多功能的自主具身智能平台,将成为引领未来新一代信息技术和人工智能发展的关键。本文从基于具身智能的移动操作机器人系统发展的需求出发,总结了基于具身智能的移动操作机器人系统的发展现状,分析了该领域发展面临的问题和挑战,提出了涵盖多模态感知技术、世界认知与理解技术、智能自主决策技术、运动与操作联合规划技术等基于具身智能的移动操作机器人系统的共性关键技术。基于此,本文从国家政策倾斜、共性技术突破、交叉学科建设与人才培养、综合验证平台构建等方面提出了对策建议,以期助力具身智能发展浪潮下我国移动操作机器人领域的长足发展。

冗余移动机械臂运动学分析及轨迹规划

针对冗余移动机械臂的轨迹规划问题,提出一种基于多项式插值法同时结合分段规划思想的方法。将机械臂与移动平台视为一个整体系统并进行运动学分析,建立运动学模型,推导了通用形式的几何雅可比矩阵及其伪逆;在轨迹规划过程中,以轨迹运行时间、移动机械臂末端移动的空间距离为优化目标,同时考虑各关节速度及加速度的约束,采用遗传算法对冗余移动机械臂的轨迹进行了优化。仿真实验结果表明,优化后运动的轨迹平滑,移动平台与机械臂各关节位移及速度曲线连续且平稳,验证了方法的可行性与有效性。

松连接运输模型下的双移动机械臂协同规划研究

针对松连接运输模型下的双移动机械臂协同运输问题,提出了一种基于事件的运动规划方法。首先,针对物体协同运输场景,对任务中系统的运输模型进行了讨论;然后,在基于事件的框架下,设计了一种基于事件的规划方法;最后,针对提出的2种运输模型,在基于事件的规划下得到了相应的运动控制率。实验结果表明:运输过程中机械臂末端之间几乎没有相对运动,并且2个方向的位置跟踪误差以及姿态误差分别控制在0.03 m,0.15 m和0.02 rad以内,因此基于事件的方法能较好地保证多机系统在运输过程中的协同性能。