Path planning in the presence of obstacles based on task requirements

We propose a novel and efficient scheme for planning a kinematically feasible path in the presence of obstacles according to task requirements. By employing geometrical analysis, we derive expressions to describe the relationship between the planned path, kinematic constraints, and obstacles in the robot workspace. The freedom available according to task requirements is then utilized to modify the infeasible portions of the planned path. We use a 6R (revolute) wrist-partitioned type of robot manipulator and a spherical obstacle as a case study to demonstrate the proposed scheme. We then extend our results to general wrist-partitioned types of robot manipulators and arbitrarily-shaped or multiple obstacles. © 1994 John Wiley & Sons, Inc.     

Two-arm kinematic posture optimization for fixtureless assembly

This article focuses on finding optimal kinematic postures for two robot arms performing various assembly tasks without the aid of jigs and fixtures. The goal of the work is to identify the manipulator postures that would result in some optimum kinematic conditions for initiating a typical male-female assembly. Specifically, the article addresses issues related to the following question: In the absence of preset jigs and fixtures, where are the optimum location in the 3-dimensional work space and the optimum orientations of the assembly parts (therefore, the postures of the manipulators holding the parts) to perform a fixtureless assembly? First, using velocity and force ellipsoids a performance criterion is developed for the optimal kinematic posture based on constraints that are imposed by the kinematic coupling of the two robot arms as well as the environment. Next, an algorithm based on a null-space search technique is formulated to “search” for the posture of the two-arm system that maximizes the performance criterion within the set of postures that satisfy given constraints. Finally, the algorithm is demonstrated numerically for two planar robots performing typical fixtureless assembly operations. © 1995 John Wiley & Sons, Inc.     

A new index of serial-link manipulator performance combining dynamic manipulability and manipulating force ellipsoids

The inertia matching ellipsoid (IME) is proposed as a new index of dynamic performance for serial-link robotic manipulators. The IME integrates the existing dynamic manipulability and manipulating-force ellipsoids to achieve an accurate measure of the dynamic torque-force transmission efficiency between the joint torque and the force applied to a load held by an end-effector. The dynamic manipulability and manipulating-force ellipsoids can both be derived from the IME as limiting forms, with respect to the weight of the load. The effectiveness of the IME is demonstrated numerically through the selection of an optimal leg posture for jumping robots and optimal active stiffness control, and experimentally through application to a pick-up task using a commercial manipulator. The index is also extended theoretically to the case of a manipulator mounted on a free-flying satellite.     

Sliding Mode Adaptive Neural-Network Control for Nonholonomic Mobile Modular Manipulators

A general mobile modular manipulator can be defined as a m-wheeled holonomic/nonholonomic mobile platform combining with a n-degree of freedom modular manipulator. This paper presents a sliding mode adaptive neural-network controller for trajectory following of nonholonomic mobile modular manipulators in task space. Dynamic model for the entire mobile modular manipulator is established in consideration of nonholonomic constraints and the interactive motions between the mobile platform and the onboard modular manipulator. Multilayered perceptrons (MLP) are used as estimators to approximate the dynamic model of the mobile modular manipulator. Sliding mode control and direct adaptive technique are combined together to suppress bounded disturbances and modeling errors caused by parameter uncertainties. Simulations are performed to demonstrate that the dynamic modeling method is valid and the controller design algorithm is effective.     

A kinetostatic index to measure the task-executing ability of robotic manipulators with limit-driven characteristics of actuators

Dexterity is an important issue for the design, trajectory planning and control of robotic manipulators. However, even though a lot of robot manipulators are driven by DC motors, no dexterity measures were introduced to evaluate how efficient a manipulator system is for performing a required task in the case of taking the limit-driven characteristics of the DC motor into consideration. In this study, we introduce a new kinetostatic dexterity index to measure the task-executing ability of robotic manipulators where the possible maximum velocity and force of the required task are derived subject to the heat-converted power limit of the DC motor. The measure is to evaluate how efficient a manipulator system is to execute a required task, while the limit-driven characteristics of its actuators are taken into consideration. Two examples are used to show that the proposed dexterity index is task-dependent and changed due to the tasks.     

Parametric motor control: A new approach to the control of point-to-point manipulator movements

We propose a control scheme for point-to-point movements of robotic manipulators, which is based on an established concept about human movement control. In this approach, actuator drive signals have an invariant shape and are parametrically modified to fit the requirements of different tasks. The appropriate parameter values are provided by an Artificial Neural Network before movement onset. Explicit solutions of the inverse kinematic and inverse dynamic equations, or multiple feedback loops, are not required for this approach. We found that Parametric Motor Control yields satisfactory performance, allowing the manipulator to discriminate between targets in a 5×3 grid and to generalize to new target locations. The new control scheme has potential benefits for scenarios where complex manipulators must be controlled in real time. © 1997 John Wiley & Sons, Inc.     

Adaptive Task-Space Control of Flexible-Joint Manipulators

This paper considers the motion control and compliance control problemsfor uncertain rigid-link, flexible-joint manipulators, and presents newadaptive task-space controllers as solutions to these problems. The motioncontrol strategy is simple and computationally efficient, requires littleinformation concerning either the manipulator or actuator/transmissionmodels, and ensures uniform boundedness of all signals and arbitrarilyaccurate task-space trajectory tracking. The proposed compliant motioncontrollers include an adaptive impedance control scheme, which isappropriate for tasks in which the dynamic character of theend-effector/environment interaction must be controlled, and an adaptiveposition/force controller, which is useful for those applications thatrequire independent control of end-effector position and contact force. Thecompliance control strategies retain the simplicity and model independenceof the trajectory tracking scheme upon which they are based, and are shownto ensure uniform boundedness of all signals and arbitrarily accuraterealization of the given compliance control objectives. The capabilities ofthe proposed control strategies are illustrated through computer simulationswith a robot manipulator possessing very flexible joints.     

基于机器视觉的非特定物体的智能抓取系统的研究

针对传统机械臂局限于按既定流程对固定位姿的特定物体进行机械化抓取,设计了一种基于机器视觉的非特定物体的智能抓取系统;系统通过特定的卷积神经网络对深度相机采集到的图像进行目标定位,并在图像上预测出一个该目标的可靠抓取位置,系统进一步将抓取位置信息反馈给机械臂,机械臂根据该信息完成对目标物体的抓取操作;系统基于机器人操作系统,硬件之间通过机器人操作系统的话题机制传递必要信息;最终经多次实验结果表明,通过改进的快速搜索随机树运动规划算法,桌面型机械臂能够根据神经网络模型反馈的的标记位置对不同位姿的非特定物体进行实时有效的抓取,在一定程度上提高了机械臂的自主能力,弥补了传统机械臂的不足.     

An Adaptive Regulator of Robotic Manipulators in the Task Space

This note addresses the problem of position control of robotic manipulators both nonredundant and redundant in the task space. A computationally simple class of task space regulators consisting of a transpose adaptive Jacobian controller plus an adaptive term estimating generalized gravity forces is proposed. The Lyapunov stability theory is used to derive the control scheme. The conditions on controller gains ensuring asymptotic stability are obtained herein in a form of simple inequalities including some information extracted from both robot kinematic and dynamic equations. The performance of the proposed control strategy is illustrated through computer simulations for a direct-drive arm of a SCARA type redundant manipulator with the three revolute kinematic pairs operating in a two-dimensional task space.     

Inverse Kinematics of 7-DOF Robots and Limbs by Decomposition and Approximation

The paper proposes a novel method for extremely fast inverse kinematics computation suitable for fast-moving manipulators and their path planning and for the animation of anthropomorphic limbs. In a preprocessing phase, the workspace of the robot is decomposed into small cells, and data sets for joint angle vectors (configurations) and hand positions/orientations (postures) are generated randomly in each cell using the forward kinematics. Due to the existence of multiple solutions for a desired posture, data classification is utilized to identify various solutions. The generated and classified data are used to determine the parameters of a simple linear or quadratic model that closely approximates the inverse kinematics within a cell. These parameters are stored in a lookup file. During the online phase, given the desired posture, the index of the appropriate cell is found, the model parameters are retrieved, and the joint angle vectors are computed. The advantages of the proposed method over the existing approaches are discussed. Data resulting from many trial runs are compiled for a manipulator and an anthropomorphic arm to demonstrate the performance of the proposed method.     

Aerial cooperative transporting and assembling control using multiple quadrotor–manipulator systems

In this paper, a fully distributed control scheme for aerial cooperative transporting and assembling is proposed using multiple quadrotor–manipulator systems with each quadrotor equipped with a robotic manipulator. First, the kinematic and dynamic models of a quadrotor with multi-Degree of Freedom (DOF) robotic manipulator are established together using Euler–Lagrange equations. Based on the aggregated dynamic model, the control scheme consisting of position controller, attitude controller and manipulator controller is presented. Regarding cooperative transporting and assembling, multiple quadrotor–manipulator systems should be able to form a desired formation without collision among quadrotors from any initial position. The desired formation is achieved by the distributed position controller and attitude controller, while the collision avoidance is guaranteed by an artificial potential function method. Then, the transporting and assembling tasks request the manipulators to reach the desired angles cooperatively, which is achieved by the distributed manipulator controller. The overall stability of the closed-loop system is proven by a Lyapunov method and Matrosov's theorem. In the end, the proposed control scheme is simplified for the real application and then validated by two formation flying missions of four quadrotors with 2-DOF manipulators.     

Task-Space Modular Dynamics for Dual-Arms Expressed through a Relative Jacobian

This paper presents modular dynamics for dual-arms, expressed in terms of the kinematics and dynamics of each of the stand-alone manipulators. The two arms are controlled as a single manipulator in the task space that is relative to the two end-effectors of the dual-arm robot. A modular relative Jacobian, derived from a previous work, is used which is expressed in terms of the stand-alone manipulator Jacobians. The task space inertia is expressed in terms of the Jacobians and dynamics of each of the stand-alone manipulators. When manipulators are combined and controlled as a single manipulator, as in the case of dual-arms, our proposed approach will not require an entirely new dynamics model for the resulting combined manipulator. But one will use the existing Jacobians and dynamics model for each of the stand-alone manipulators to come up with the dynamics model of the combined manipulator. A dual-arm KUKA is used in the experimental implementation.     

Linearized dynamic models of robot manipulators in cartesian space

This article presents development of the linearized dynamic models of robot manipulators in Cartesian space. A clever method is proposed to formulate the linearized dynamic models of robot manipulators in Cartesian space. Efficient methods are developed to compute various matrices involved in the models (or the manipulator sensitivity matrices in Cartesian space), such as the Jacobian matrix and the first and second derivatives of it with respect to time as well as the manipulator sensitivity matrices in joint space. The proposed methods are simple and systematic and have computational complexity of the order O(n²) only, where n is the number of degrees-of-freedom of the manipulator.     

Task-based configuration control of redundant manipulators

This article establishes new goals for redundancy resolution based on manipulator dynamics and end-effector characteristics. These goals can be accomplished by employing the recently developed configuration control approach. Redundancy resolution is achieved by controlling the joint inertia matrix or the end-effector mass matrix that affect the inertial torques or by reducing the joint torques due to gravity loading and payload. The manipulator mechanical advantage and velocity ratio are also used as performance measures to be improved by proper utilization of redundancy. Furthermore, end-effector compliance, sensitivity, and impulsive force at impact are introduced as redundancy-resolution criteria. The new goals for redundancy resolution presented in this article allow a more efficient utilization of the redundant joints based on the desired task requirements. Simple case studies using computer simulations are described for illustration.     

The power manipulability – A new homogeneous performance index of robot manipulators

Jacobian-based performance indices such as the manipulability ellipsoid, the condition number and the minimum singular value, have been very helpful tools both for mechanical manipulator design and for determining suitable manipulator postures to execute a given task. For a manipulator having complex degrees of freedom (translations and rotations), Jacobian matrix becomes non-homogeneous, i.e. it contains elements with different physical units; therefore, the evaluation of its determinant, eigenvalues or singular values needs the combination of quantities of different nature, which is physically inconsistent and moreover it corresponds to a noncommensurable system. In this paper, a new performance index of robot manipulators is proposed. It is fully homogeneous and it constitutes a physically consistent system whether the manipulator contains joints of different natures, or the task space combines both translation and rotation motion. The development is concerned with the study of power within the mechanism. Given that the power has the same physical units in translation and rotation, it can be used as a homogeneous or natural performance index of manipulators by examining the behaviour of its basic components namely, force and speed, at different kinematics configurations. Furthermore, the new concept of vectorial power is introduced, followed by to the quadrivector of apparent power, and leading to the final homogeneous performance index of the power manipulability (PM). This new approach matches perfectly with mechanisms having joints of different natures, as well as with a task space combining both translation and rotation.     

冗余机器人的双向自运动路径规划

冗余机器人的自运动路径规划是在保持手端任务向量不变的情况下,在关节空间内寻找一条连接机器人初始关节构形和期望关节构型的几何路径.本文给出一种双向自运动路径规划算法,其基本思想是使位于初始关节构形的真实机器人和位于期望关节构形的虚拟机器人在自运动流形上运动并收敛到同一关节构形,从而得到一条连接初始和期望关节构形的自运动几何路径.该算法克服了以往算法容易陷入局部极小构形的缺陷.仿真结果证实了算法的有效性.     

An efficient algorithm for generating manipulator inertia matrix using the minimum set of dynamics parameters

This article presents an efficient algorithm for computing the inertia matrix of rigid serial manipulators. The derivation of the algorithm is based on the closed-form formulation of the force and moment exerted on a link using a minimum set of dynamic parameters of the manipulator model. The minimum set of dynamic parameters can be derived completely from the original dynamic parameters using the recursive re-grouping method before starting the simulation and the control. The proposed computation method is suitable for the control and the simulation based on parameter estimates because the minimum set of dynamic parameters is an identifiable parameter set. The computational efficiency of the proposed methods is compared with other published methods. It is shown that the proposed algorithm is the most efficient approach for serial manipulators. As an example, the number of computations for the inertia matrix of a manipulator with n rotational joints is 11n²+9 n − 35 multiplications and 7n²+ 23 n − 57 additions by reformulating the dynamic model using the minimum set of dynamic parameters. © 1996 John Wiley &, Sons, Inc.     

Dynamic Modeling and Tracking Control of a Nonholonomic Wheeled Mobile Manipulator with Dual Arms

This paper presents methodologies for dynamic modeling and trajectory tracking of a nonholonomic wheeled mobile manipulator (WMM) with dual arms. The complete dynamic model of such a manipulator is easily established using the Lagrange’s equation and MATHEMATICA. The structural properties of the overall system along with its subsystems are also well investigated and then exploited in further controller synthesis. The derived model is shown valid by reducing it to agree well with the mobile platform model. In order to solve the path tracking control problem of the wheeled mobile manipulator, a novel kinematic control scheme is proposed to deal with the nonholonomic constraints. With the backstepping technique and the filtered-error method, the nonlinear tracking control laws for the mobile manipulator system are constructed based on the Lyapunov stability theory. The proposed control scheme not only achieves simultaneous trajectory and velocity tracking, but also compensates for the dynamic interactions caused by the motions of the mobile platform and the two onboard manipulators. Simulation results are performed to illustrate the efficacy of the proposed control strategy.     

Collision: Modeling,simulation and identification of robotic manipulators interacting with environments

The performance of many robotic tasks depends greatly on their dynamic collision behavior. This article presents a simple method for modeling and simulating collision behavior in manipulators. The main goal in this task is to provide informative contact models. The proposed models encompasscollision attributes which comprise not only (local) contact surface properties but also structural properties of the environmental object and the manipulator. With this method, the entire dynamic and interactive motion of the manipulator with the environmental object can be simulated effectively. This is verified by our simulation results. To facilitate our investigation, a 2 DOF planar elbow manipulator with PD control is considered in the simulations as well as theoretical analysis. The simulation results are used to highlight the collision attributes which affect collision behavior and to study the effects of these attributes on the manipulator-work environment safety and performance. On the other hand, the reliable operation of intelligent robotic systems in unstructured environments requires the estimation of collision attributes before the prediction of the collision behavior can be completed. For this purpose, we introduce the notion ofcollision identification. The present paper introduces a framework for collision identification in robotic tasks. The proposed framework is based on Artificial Neural Networks (ANNs) and provides fast and relatively reliable identification of the collision attributes. The simulation results are used to generate training data for the set of ANNs. A modularized ANN-based architecture is also developed to reduce the training effort and to increase the accuracy of ANNs. The test results indicate the satisfactory performance of the proposed collision identification system.     

A framework for large‐force task planning of mobile and redundant manipulators

A framework tackling the problem of large wrench application using robotic systems with limited force or torque actuators is presented. It is shown that such systems can apply a wrench to a limited set of Cartesian locations called force workspace (FW), and its force capabilities are improved by employing base mobility and redundancy. An efficient numerical algorithm based on 2ⁿ‐tree decomposition of Cartesian space is designed to generate FW. Based on the FW generation algorithm, a planning method is presented resulting in proper base positioning relative to large‐force quasistatic tasks. Additionally, the case of tasks requiring application of a wrench along a given path is considered. Task workspace, the set of Cartesian space locations that are feasible starting positions for such tasks, is shown to be a subset of FW. This workspace is used for identifying proper base or task positions guaranteeing task execution along desired paths. Finally, to plan redundant manipulator postures during large‐force‐tasks, a new method based on a min–max optimization scheme is developed. Unlike norm‐based methods, this method guarantees no actuator capabilities are exceeded, and force or torque of the most loaded joint is minimized. Illustrative examples are given demonstrating validity and usefulness of the proposed framework. ©1999 John Wiley & Sons, Inc.