Kinematics of Robot Fingers with Circular Rolling Contact Joints

This paper examines the kinematics of robot fingers that use RR subassemblies coupled by rolling contact to provide versatile one degree‐of‐freedom mechanical joints. A three degree‐of‐freedom robot finger constructed with these joints is a 6R planar chain with the R‐joints coupled together in pairs. The focus is on coupling based on pure rolling of circular cylinders which can be realized by friction contact, gearing, or cable tendons. We derive the forward, inverse and rate kinematics for this 3(RR) open chain. We then focus on the two degree‐of‐freedom 2(RR) case to illustrate the geometry of the system. An example design of a robot finger that incorporates these joints in order to provide compact movement is provided. © 2003 Wiley Periodicals, Inc.     

Vision-Based Robotic Motion Control for Non-autonomous Environment

A visual servo control system with SOPC structure is implemented on a retrofitted Mitsubishi Movemaster RV-M2 robotic system. The hardware circuit has the functions of quadrature encoder decoding, limit switch detecting, pulse width modulation (PWM) generating and CMOS image signal capturing. The software embedded in Nios II micro processor has the functions of using UART to communicate with PC, robotic inverse kinematics calculation, robotic motion control schemes, digital image processing and gobang game AI algorithms. The digital hardware circuits are designed by using Verilog language, and programs in Nios II micro processor are coded with C language. An Altera Statrix II EP2S60F672C5Es FPGA chip is adopted as the main CPU of the development board. A CMOS color image sensor with 356 ×292 pixels resolution is selected to catch the environment time-varying change for robotic vision-based servo control. The system performance is evaluated by experimental tests. A gobang game is planned to reveal the visual servo robotic motion control objective in non-autonomous environment. Here, a model-free intelligent self-organizing fuzzy control strategy is employed to design the robotic joint controller. A vision based trajectory planning algorithm is designed to calculate the desired angular positions or trajectory on-line of each robotic joint. The experimental results show that this visual servo control robot has reliable control actions.     

Coordinated Motion and Force Control of Multi-Limbed Robotic Systems

This analytic and experimental study proposes a control algorithm for coordinated position and force control for autonomous multi-limbed mobile robotic systems. The technique is called Coordinated Jacobian Transpose Control (CJTC). Such position/force control algorithms will be required if future robotic systems are to operate effectively in unstructured environments. Generalized Control Variables (GCVs), express in a consistent and coordinated manner the desired behavior of the forces exerted by the multi-limbed robot on the environment and a system's motions. The effectiveness of this algorithm is demonstrated in simulation and laboratory experiments on a climbing system.     

Motion Planning Algorithms for a Rolling Sphere With Limited Contact Area

The paper deals with the motion planning problem for a rolling sphere with limited contact area. The system under consideration is represented by a hemispherical object that can roll without slipping or spinning on the plane. Under the constraints imposed on the size of the contact area, the construction of motion can be regarded as a problem of parallel parking in a finite number of movement steps. A motion strategy, realizing the movement steps by tracing generalized figure eights on the hemisphere, is introduced. Two different algorithms for this motion strategy, the circle-based and the generalized Viviani-curve-based ones, are proposed. The convergence of the algorithms is analyzed, and the computational feasibility of these algorithms is verified under simulation.     

A Framework for Automatic Generation of a Contact State Graph for Robotic Assembly

Dynamic manipulation of an active object is introduced as a general model of hopping and juggling tasks. In this setting, juggling and hopping are two extreme cases of this general model. Behavioral resemblance of these two tasks is afterwards extended to a detailed mathematical analogy between them. Then the analogy is exploited to develop a unified and abstract planning framework for juggling and hopping. To this end, dynamic manipulation of an active object is decomposed into three distinct phases and two transitions: Carry I, Free flight and Carry II phases. These phases are analogous to Lift off, Free flight and Touch down in hopping. In the next step, a mathematical model for each phase is developed. It is shown that dynamic grasp (in Carry phases of juggling) and foot stability (in Support phases of hopping) conditions share similar sets of dynamic equations. Accordingly, Lift off/Release and Touch down/Catch conditions in hopping/juggling are derived. It is shown that analogous strategies can be developed for Lift off and Release. The analogy is held for Touch down and Catch conditions as well. It is discussed that in the planning framework the initial and the goal configurations of the three phases are set in a model-based and forward manner. To do so, Touch down/Landing time, Free flight duration and robot/object maneuvers during Free flight are used as free parameters for planning in order to ensure foot stability in hopping and dynamic grasp in juggling along with other constraints.     

Robust Motion Control for Robotic Assembly Tasks using Variable Structure Control Scheme

The success of robot assembly tasks depends heavily on its ability to handle the interactions which take place between the parts being assembled. In this paper, a robust motion-control method is presented for robot manipulators performing assembly tasks in the presence of dynamic constraints from the environment. Using variable structure model reaching control concept, the control objectives is first formulated as a performance model in the task space. A dynamic compensator is then introduced to form the switching function such that the sliding-mode matches the desired model. A simple variable structure control law is suggested to force the system to reach and stay on the sliding mode so that the specified model is achieved.The proposed method is applied to control the prismatic joint of a selective compliance assembly robot-arm type robot for the insertion of printed circuit board into an edge connector socket. Various amounts of interaction forces are generated during the operation. Experimental and simulation results demonstrated the performance of the variable structure model reaching control approach. In comparison, it is shown that the popular position controllers such as proportional plus derivative control and proportional plus derivative with model-based feedforward control are not suitable for achieving good trajectory tracking accuracy in assembly tasks which experience potential interaction force.     

机器人液压挖掘机运动系统的建模与控制

首先利用机器人运动学将铲斗的理想运动轨迹和各工作装置的目标转角序列联系起来,然后利用拉格朗日方程建立各工作装置的运动学模型,最后推导出LUDV液压驱动系统的电液模型,从而得到了挖掘机器人运动系统的完整模型．针对系统动力学的高非线性、参数的不确定性、外界干扰及比例方向阀的死区及非线性增益等特点,提出一种建立在自适应鲁棒控制基础上的非连续映射方法来处理运动系统并利用鲁棒反馈来消除近似误差．最后利用动臂控制试验来验证控制方法的正确性．     

用OpenGL构造机器人灵巧手虚拟场景

论述了用OpenGL绘制三指九关节机器人灵巧手虚拟场景,加上了光照、反走样、融合、雾化等效果处理,使图形更逼真。并且编写了一个串行通信程序,使灵巧手虚拟场景能接收灵巧手控制发送过来的数据,使虚拟场景能和巧手实现同步运动。     

基于CFD的仿鲹科机器鱼动力学建模与运动控制

仿生机器鱼的运动控制是仿生机器鱼推广应用的基础;然而,仿鲹科机器鱼的推进一般采用鱼体波数据,很少采用真实鱼类游动数据;为了深入探究仿鲹科机器鱼运动控制方法,采用了计算流体力学方法,通过标定流体介质、来流速度、鱼体几何形状等措施,利用Fluent软件进行了建模,然后针对鱼体波数据和真实金枪鱼游动采样数据两种不同推进数据对仿生机器鱼进行了仿真和实验;结果表明对于多关节仿生机器鱼推进方面,真实金枪鱼游动采样数据相较于常见的鱼体波产生的推进数据,在躯干进行大幅值摆动的情况下效果更好;这一仿真和实验对比为仿鲹科机器鱼的高效运动控制提供了一种新思路。     

The Application of Connectionist Structures to Learning Impedance Control in Robotic Contact Tasks

The goal of this paper is to consider the synthesis of learning impedance control using recurrent connectionist structures for on-line learning of robot dynamic uncertainties in the case of robot contact tasks. The connectionist structures are integrated in non-learning impedance control laws that are intended to improve the transient dynamic response immediately after the contact. The recurrent neural network as a part of hybrid learning control algorithms uses fast learning rules and available sensor information in order to improve the robotic performance progressively for a minimum possible number of learning epochs. Some simulation results of deburring process with the MANUTEC r3 robot are presented here in order to verify the effectiveness of the proposed control learning algorithms.     

Control of Angular Motion of the Robotic Space Module Transporting a Flexible Load

Consideration was given to designing the optimal control of a free-flying robotic space module equipped with relay actuators which carries a bulky flexible load. The procedure of designing a spatial modal-physical model of the robotic space module with a flexible load was described. For this construction, numerical analysis of the dynamic portrait which accompanies the model enables one to establish the profile of its elastic oscillations which has the form of a multiextremal function in the space of possible values of the coordinate of the point where the load is gripped by the manipulator. The global extremum (minimum) of this dependence, which was accepted as the goal function, was used as a criterion for designing the algorithm optimizing the gripper position on the load axis upon stabilizing the angular motion of the module. The calculated extremum is used in the loop of adaptive adjustment of the gripper parameter, which prevents resonance swinging of the flexible load transported to the place of installation.     

基于LabVIEW的滚动接触疲劳试验测控系统

针对现有疲劳寿命试验机存在异常停机、无远程监控和试验数据保存不完整等问题,对其基于LabVIEW的测控系统进行了改进,增加了智能停机、远程监控、数据分块保存等功能模块,并对改进后的测控系统进行了基于滚动轴承磷化处理项目的试验测试,试验结果表明:改进后的测控系统解决了上述问题,在实现其基本功能的同时提高了试验效率、扩展了试验机功能,提高了试验机的测控性能,为滚动接触疲劳寿命的研究提供了有力的技术支持。     

Analysis and Verification of Repetitive Motion Planning and Feedback Control for Omnidirectional Mobile Manipulator Robotic Systems

Mobile manipulator robotic systems (MMRSs) composed of a manipulator and a mobile platform are investigated in this paper. In order for the mobile manipulator robotic system (MMRS) to return to its initial state when the manipulator’s end-effector is requested to execute cyclical tasks, a quadratic program (QP) based repetitive motion planning and feedback control (RMPFC) scheme is proposed and analyzed. Such an RMPFC scheme can not only mix motion planning and reactive control, but also consider the physical limits of the robotic system. Mathematically, the efficacy of the RMPFC scheme is verified via gradient dynamics analysis. To further demonstrate the effectiveness of the RMPFC scheme, a kinematically redundant MMRS composed of a three degrees-of-freedom (DOF) planar manipulator and an omnidirectional mobile platform is designed, modeled and analyzed. Then, repetitive motion planning and feedback control for the designed omnidirectional MMRS is studied. Besides, a numerical algorithm is developed and presented to solve the QP and resolve the redundancy of the robotic system. Moreover, computer simulations are comparatively performed on such an omnidirectional MMRS, and simulation results substantiate the effectiveness, accuracy and superiority of the proposed RMPFC scheme.     

基于Robotics Toolbox的机器人分步速度控制仿真研究

分步速度控制方法是利用雅可比矩阵计算关节速度以得到预定的笛卡尔速度。文章首先介绍了分步速度控制方法,然后在Matlab环境下,利用Robotics Toolbox建立了平面3R机器人,最后编写M文件对该机器人进行了分步速度控制仿真。通过仿真,得到了机器人各个关节的运动与时间的关系,实现了预定的目标,进而验证了分步速度控制方法的正确性和可行性。     

Modeling and Adaptive Neural Network Control for a Soft Robotic Arm With Prescribed Motion Constraints

This paper presents a dynamic model and performance constraint control of a line-driven soft robotic arm. The dynamics model of the soft robotic arm is established by combining the screw theory and the Cosserat theory. The unmodeled dynamics of the system are considered, and an adaptive neural network controller is designed using the backstepping method and radial basis function neural network. The stability of the closed-loop system and the boundedness of the tracking error are verified using Lyapunov theory. The simulation results show that our approach is a good solution to the motion constraint problem of the line-driven soft robotic arm.      

Robotic Motion Using Harmonic Functions and Finite Elements

The harmonic functions have proved to be a powerful technique for motion planning in a known environment. They have two important properties: given an initial point and an objective in a connected domain, a unique path exists between those points. This path is the maximum gradient path of the harmonic function that begins in the initial point and ends in the goal point. The second property is that the harmonic function cannot have local minima in the interior of the domain (the objective point is considered as a border). This paper proposes a new method to solve Laplace’s equation. The harmonic function solution with mixed boundary conditions provides paths that verify the smoothness and safety considerations required for mobile robot path planning. The proposed approach uses the Finite Elements Method to solve Laplace’s equation, and this allows us to deal with complicated shapes of obstacles and walls. Mixed boundary conditions are applied to the harmonic function to improve the quality of the trajectories. In this way, the trajectories are smooth, avoiding the corners of walls and obstacles, and the potential slope is not too small, avoiding the difficulty of the numerical calculus of the trajectory. Results show that this method is able to deal with moving obstacles, and even for non-holonomic vehicles. The proposed method can be generalized to 3D or more dimensions and it can be used to move robot manipulators.     

Optimal Motion Planning of Robotic Manipulators Removing Mobile Objects Grasped in Motion

The following study deals with motion optimization of robot arms having to transfer mobile objects grasped when moving. This approach is aimed at performing repetitive transfer tasks at a rapid rate without interrupting the dynamics of both the manipulator and the moving object. The junction location of the robot gripper with the object, together with grasp conditions, are partly defined by a set of local constraints. Thus, optimizing the robot motion in the approach phase of the transfer task leads to the statement of an optimal junction problem between the robot and the moving object. This optimal control problem is characterized by constrained final state and unknown traveling time. In such a case, Pontryagin"s maximum principle is a powerful mathematical tool for solving this optimization problem. Three simulated results of removing a mobile object on a conveyor belt are presented; the object is grasped in motion by a planar three-link manipulator.     

Identification of Contact Dynamics Parameters for Stiff Robotic Payloads

This paper investigates and demonstrates the feasibility of identifying contact dynamics parameters for stiff robotic payloads using a robotic system. The contact dynamics model for stiff payloads is motivated, and theoretical parameter values and bounds are provided. Then, the effect of nonidealities such as surface roughness and plastic deformation on the theoretical values is demonstrated. A row-wise-scaled total least-squares parameter estimation algorithm is proposed and applied to experimental data measured using the special purpose dexterous manipulator task verification facility manipulator at the Canadian Space Agency. The experimental results are compared to a separate set of experiments with a material testing machine as well as finite-element modeling results. Finally, the experimental findings are generalized by providing guidelines for the maximum identifiable payload stiffness as a function of the position resolution, the maximum exertable force, and the structural stiffness of the robotic system.     

Distributed Motion Constraints for Algebraic Connectivity of Robotic Networks

This paper studies connectivity maintenance of robotic networks that communicate at discrete times and move in continuous space. We propose a distributed coordination algorithm that allows the robots to decide whether a desired collective motion breaks connectivity. We build on this procedure to design a second coordination algorithm that allows the robots to modify a desired collective motion to guarantee that connectivity is preserved. These algorithms work under imperfect information caused by delays in communication and the robots’ mobility. Under very outdated information, the proposed algorithms might prevent some or all of the robots from moving. We analyze the correctness of our algorithms by formulating them as games against a hypothetical adversary who chooses system states consistent with observed information. The technical approach combines tools from algebraic graph theory, linear algebra, and nonsmooth analysis.