Hybrid Force and Vision-Based Contour Following of Planar Robots

Manipulators interacted with uncalibrated environments have limited dexterity due to constraints imposed by unknown environments. However, to perform science or industrial operations, it is necessary to be able to position and orient these manipulators on targets in order to accomplish required control tasks. This article describes how one might enhance manipulator dexterity for planar contour following tasks using hybrid force and vision-based control. The proposed control approach can guarantee task precision employing only a single-axis force sensor and an imprecisely calibrated CCD camera whose optical axis is perpendicular to the planar workspace. The goal of the autonomous task is to drive an instrument mounted on the end-effector of a planar robotic manipulator to follow a visually determined planar contour and continue tracking the contour in desired pose, contact force, and speed, all demanding time-varying, with precision. The proposed control architecture is suitable for applications that require simultaneous force and pose control in unknown environments. Our approach is successfully validated in a real task environment by performing experiments with an industrial robotic manipulator.     

Fuzzy-based-admittance controller for safe natural human–robot interaction

ABSTRACT

In recent years, a great amount of research on physical human–robot interaction has been conducted, and mainly concentrated on safety issues to minimize the risk of accidents to the operator during the cooperation between human and robot. Unfortunately, the identification of inertia and damping matrices in the dynamic admittance model is time-consuming, which is still an open problem of previous admittance controllers. Additionally, the natural cooperation is that cooperative movements are implemented in every degree of freedom in space, which is rarely concerned while it is important to implement more complex cooperative movements, and to help operator feels naturally during the cooperation. This paper presents an alternative admittance controller based on inference mechanism of fuzzy logic to eliminate the identification of inertia and damping matrices during the process of controller formulation in which the end-effector’s velocity is adaptively adjusted via external wrench (force/torque measured by a sensor mounted on end-effector) and power transmitted by the robot. Moreover, the proposed controller also considers end-effector’s full DOF to guarantee the natural human–robot interaction. The fuzzy-admittance controller is evaluated by an experimental set-up of teaching task using 6-DOF manipulator in which manipulator moves passively via the human impact on real-time force/torque sensor mounted on end-effector.     

Intelligent and Efficient Strategy for Unstructured Environment Sensing Using Mobile Robot Agents

In field environments it is not usually possible to provide robots in advance with valid geometric models of its task and environment. The robot or robot teams need to create these models by scanning the environment with its sensors. Here, an information-based iterative algorithm to plan the robot's visual exploration strategy is proposed to enable it to most efficiently build 3D models of its environment and task. The method assumes mobile robot (or vehicle) with vision sensors mounted at a manipulator end-effector (eye-in-hand system). This algorithm efficiently repositions the systems' sensing agents using an information theoretic approach and fuses sensory information using physical models to yield a geometrically consistent environment map. This is achieved by utilizing a metric derived from Shannon's information theory to determine optimal sensing poses for the agent(s) mapping a highly unstructured environment. This map is then distributed among the agents using an information-based relevant data reduction scheme. This method is particularly well suited to unstructured environments, where sensor uncertainty is significant. Issues addressed include model-based multiple sensor data fusion, and uncertainty and vehicle suspension motion compensation. Simulation results show the effectiveness of this algorithm.     

An adaptive observer for a spacecraft–manipulator system using a camera mounted on its spacecraft

This paper deals with a motion control system for a space robot with a manipulator. Many motion controllers require the positions of the robot body and the manipulator hand with respect to an inertial coordinate system. In order to measure them, a visual sensor using a camera is frequently used. However, there are two difficulties in measuring them by means of a camera. The first one is that a camera is mounted on the robot body, and hence it is difficult to directly measure the position of the robot body by means of it. The second one is that the sampling period of a vision system with a general-purpose camera is much longer than that of a general servo system. In this paper, we develop an adaptive state observer that overcomes the two difficulties. In order to investigate its performance, we design a motion control system that is constructed by combining the observer with a PD control input, and then conduct numerical simulations for the control system. Simulation results demonstrate the effectiveness of the proposed observer.     

Robotic motion planning and manipulation in an uncalibratedenvironment

The authors analyze planning and control problems in “robotic manipulation” in an uncalibrated environment consisting of a PUMA 560 robotic manipulator, a rotating turntable equipped with an encoder and a CCD camera based vision sensor fixed permanently on the ceiling. It is assumed that a part with a known shape but unknown orientation is placed on the turntable which is rotating with an unknown motion dynamics. Furthermore, the calibration parameters are a priori assumed to be unknown. The objective is to track the rotating part with an a priori specified relative orientation. The task considered is of importance in various problems concerning industrial automation, such as part-feeding and tool-changing     

Path-constrained control of a redundant manipulator in a task space

This study addresses the problem of controlling a redundant manipulator with both state and control dependent constraints. The task of the robot is to follow by the end-effector a prescribed geometric path given in the task space. The control constraints resulting from the physical abilities of robot actuators are also taken into account during the robot movement. Provided that a solution to the aforementioned robot task exists, the Lyapunov stability theory is used to derive the control scheme. The numerical simulation results, carried out for a planar manipulator whose end-effector follows a prescribed geometric path given in a task space, illustrate the trajectory performance of the proposed control scheme.     

Experiments in contact control

This article describes the implementation, experimentation, and application of contact control schemes for a 7-DOF Robotics Research arm. The contact forces and torques are measured in the sensor frame by the 6-axis force/torque sensor mounted at the wrist, are compensated for gravity, and then are transformed to the tool frame in which the contact task is defined and executed. The contact control schemes are implemented on the existing robot Cartesian position control system at 400Hz, do not require force rate information, and are extremely simple and computationally fast. Three types of contact control schemes are presented: compliance control, force control, and dual-mode control. In the compliance control scheme, the contact force is fed back through a lag-plus-feedforward compliance controller so that the end-effector behaves like a spring with adjustable stiffness; thus the contact force can be controlled by the reference position command. In the force control scheme, a force setpoint is used as the command input and a proportional-plus-integral force controller is employed to ensure that the contact force tracks the force setpoint accurately. In the dual-mode control scheme, the end-effector approaches and impacts the reaction surface in compliance mode, and the control scheme is then switched automatically to force mode after the initial contact has been established. Experimental results are presented to demonstrate contact with hard and soft surfaces under the three proposed control schemes. The article is concluded with the application of the proposed schemes to perform a contact-based eddy-current inspection task. In this task, the robot first approaches the inspection surface in compliance control until it feels that it has touched the surface, and then automatically levels the end-effector on the surface. The robot control system then transitions to force control and applies the desired force on the surface while executing a scanning motion. At the completion of the inspection task, the robot first relaxes the applied force and then retracts from the surface. © 1996 John Wiley & Sons, Inc.     

Behavioristic image-based pose control of mobile manipulators using an uncalibrated eye-in-hand vision system

In the execution of material handling, the mobile manipulator is controlled to reach a station by its mobile base. This study adopts an uncalibrated eye-in-hand vision system to provide visual information for the manipulator to pick up a workpiece on the station. A novel vision-guided control strategy with a behavior-based look-and-move structure is proposed. This strategy is based on six image features, predefined by image moment method. In the designed neural-fuzzy controllers with varying learning rate, each image feature error is taken to generate intuitively one DOF motion command relative to the camera coordinate frame using fuzzy rules, which define a particular visual behavior. These behaviors are then fused to produce a final command action to perform grasping tasks using the proposed behavior fusion scheme. Finally, the proposed control strategy is experimentally applied to control the end-effector to approach and grasp a workpiece in various locations on a station.     

Data-Driven Human-Robot Interaction Without Velocity Measurement Using Off-Policy Reinforcement Learning

In this paper,we present a novel data-driven design method for the human-robot interaction(HRI)system,where a given task is achieved by cooperation between the human and the robot.The presented HRI controller design is a two-level control design approach consisting of a task-oriented performance optimization design and a plant-oriented impedance controller design.The task-oriented design minimizes the human effort and guarantees the perfect task tracking in the outer-loop,while the plant-oriented achieves the desired impedance from the human to the robot manipulator end-effector in the inner-loop.Data-driven reinforcement learning techniques are used for performance optimization in the outer-loop to assign the optimal impedance parameters.In the inner-loop,a velocity-free filter is designed to avoid the requirement of end-effector velocity measurement.On this basis,an adaptive controller is designed to achieve the desired impedance of the robot manipulator in the task space.The simulation and experiment of a robot manipulator are conducted to verify the efficacy of the presented HRI design framework.     

一种机器人手眼关系自标定方法

设计了一种基于场景中单个景物点的机器人手眼关系标定方法．精确控制机械手末端执行器做 5 次以上平移运动和2 次以上旋转运动,摄像机对场景中的单个景物点进行成像．通过景物点的视差及深度 值反映摄像机的运动,建立机械手末端执行器与摄像机两坐标系之间相对位置的约束方程组,线性求得摄像 机内参数及手眼关系．标定过程中只需提取场景中的一个景物点,无需匹配,无需正交运动,对机械手的运 动控制操作方便、算法实现简洁．模拟数据实验与真实图像数据实验结果表明该方法可行、有效．     

Path following by the end-effector of a redundant manipulator operating in a dynamic environment

This paper addresses the problem of generating at the control-loop level a collision-free trajectory for a redundant manipulator operating in dynamic environments which include moving obstacles. The task of the robot is to follow, by the end-effector, a prescribed geometric path given in the work space. The control constraints resulting from the physical abilities of robot actuators are also taken into account during the robot movement. Provided that a solution to the aforementioned robot task exists, the Lyapunov stability theory is used to derive the control scheme. The numerical simulation results for a planar manipulator whose end-effector follows a prescribed geometric path, given in both an obstacle-free work space and a work space including the moving obstacles, illustrate the trajectory performance of the proposed control scheme.     

Collaborative Multi-MSA Multi-Target Tracking and Surveillance: a Divide &; Conquer Method Using Region Allocation Trees

This work deals with the problem of the accurate task space control subject to finite-time convergence. Kinematic and dynamic equations of a rigid robotic manipulator are assumed to be uncertain. Moreover, unbounded disturbances, i.e., such structures of the modelling functions that are generally not bounded by construction, are allowed to act on the manipulator when tracking the trajectory by the end-effector. Based on suitably defined task space non-singular terminal sliding vector variable and the Lyapunov stability theory, we derive a class of absolutely continuous (chattering-free) robust controllers based on the estimation of a Jacobian transpose matrix, which seem to be effective in counteracting uncertain both kinematics and dynamics, unbounded disturbances and (possible) kinematic and/or algorithmic singularities met on the robot trajectory. The numerical simulations carried out for a 2DOF robotic manipulator with two revolute kinematic pairs and operating in a two-dimensional task space, illustrate performance of the proposed controllers.     

Intelligent compliant force/motion control of nonholonomic mobile manipulator working on the nonrigid surface

The task under consideration is to control a mobile manipulator for the class of nonrigid constrained motion. The working surface is deformable. The geometric and physical model of the surface is unknown and all contact force is nonlinear and difficult to model. To accomplish a task of this kind, we propose a force/motion fuzzy controller based on the philosophy of the parallel approach in two decoupled subspaces. In one subspace, we control the constant contact force normal to the surface and estimate the end-effector tool’s deformable depth of the surface; in the other, we keep the end-effector’s constant velocity parallel to the tangential plane of the surface and suppress the tangential force of the surface deformation. The nonholonomic mobile base is utilized to avoid the singularity. Stability is established and conditions for the control parameters are derived. Performance of the proposed controller is verified through computer simulations compared with the model-based control.     

Singularity robust path planning for real time base attitude adjustment of free-floating space robot

This paper presents a singularity robust path planning for space manipulator to achieve base (satellite) attitude adjustment and end-effector task. The base attitude adjustment by the movement of manipulator will save propellant compared with conventional attitude control system. A task-priority reaction null-space control method is applied to achieve the primary task of adjusting attitude and secondary task of accomplishing end-effector task. Furthermore, the algorithm singularity is eliminated in the proposed algorithm compared with conventional reaction null-space algorithm. And the singular value filtering decomposition is introduced to dispose the dynamic singularity, the unit quaternion is also introduced to overcome representation singularity. Hence, a singularity robust path planning algorithm of space robot for base attitude adjustment is derived. A real time simulation system of the space robot under Linux/RTAI (realtime application interface) is developed to verify and test the feasibility and reliability of the method. The experimental results demonstrate the feasibility of online base attitude adjustment of space robot by the proposed algorithm.     

A review on vision-based control of flexible manipulators

In this review, recent developments in the field of flexible robot arm control using visual servoing are reviewed. In comparison to rigid robots, the end-effector position of flexible links cannot be obtained precisely enough with respect to position control using kinematic information and joint variables. To solve the task here the use of a vision sensor (camera) system, visual servoing is proposed to realize the task of control flexible manipulators with improved quality requirements. The paper is organized as follows: the visual servoing architectures will be reviewed for rigid robots first. The advantages, disadvantages, and comparisons between different approaches of visual servoing are carried out. The using of visual servoing to control flexible robot is addressed next. Open problems such as state variables estimation as well as the combination of different sensor properties as well as some application-oriented points related to flexible robot are discussed in detail.     

Comparison of manual control methods for space manipulator positioning tasks

The Russian Segment of the International Space Station will be equipped with a 10 m long anthropomorphic space manipulator with six degrees of freedom. The robot is called the European Robot Arm, or ERA. Its hand, or end-effector, contains a camera which will be used for fine positioning of the end-effector, in order to grasp an object. At the Delft University of Technology, a human-machine interface for manual control of the ERA is being developed. The control device is a Spaceball controller, which is used to control the spatial end-effector velocity. This article describes four control methods that transform the Spaceball movements into movements in the end-effector camera picture. The control methods are compared by means of human-machine experiments. The results are also useful in many other areas of spatial manipulation, like undersea robots, robots in the nuclear industry, and minimally invasive surgery.     

利用平面单应分解实现服务机器人视觉伺服

智能空间中家庭服务机器人所需完成的主要任务是协助人完成物品的搜寻、定位与传递。而视觉伺服则是完成上述任务的有效手段。搭建了由移动机器人、机械臂、摄像头组成的家庭服务机器人视觉伺服系统,建立了此系统的运动学模型并对安装在机械臂末端执行器上的视觉系统进行了内外参数标定,通过分解世界平面的单应来获取目标物品的位姿参数,利用所获取的位姿参数设计了基于位置的视觉伺服控制律。实验结果表明,使用平面单应分解方法来设计控制律可简单有效地完成家庭物品的视觉伺服任务。     

Research on the Satellite On-Orbit Self-Servicing Testbed

The paper puts forward the concept of the Satellite On-Orbit Self-Servicing (SOOSS), which can correct the malfunctions of deployable appendages of satellites on-orbit by a on-board robot system. In order to verify this concept, a ground testbed has been presented; a robot system composed of a 4-d.o.f. manipulator and an end-effector mounted on the satellite are designed to accomplish the above operations. The main features of the robot system are mechatronics, multi-sensors and intelligent control. The structure of the modular joint is introduced in detail. The multi-finger dexterous HIT/DLR Hand is employed as the end-effector. In the SOOSS, the robot system is controlled through remote teleoperation. The virtual environment of the SOOSS has been built and experiments have been carried out to verify the feasibility of the SOOSS.     

Optimal location of a general position and orientation end-effector's path relative to manipulator's base,considering velocity performance

The objective of the present paper is to introduce an offline algorithm searching for the optimal or suboptimal placement of a robot's base during workcell design, so that its end-effector can perform a position and orientation path following task of a given 3D curved path and orientation, maximizing the manipulator's velocity performance. The global index employed for this velocity performance optimization is the approximation of the minimum manipulator velocity ratio (AMMVR).