Symmetry position/force hybrid control for cooperative object transportation using multiple humanoid robots

A symmetry position/force hybrid control framework for cooperative object transportation tasks with multiple humanoid robots is proposed in this paper. In a leader-follower type cooperation, follower robots plan their biped gaits based on the forces generated at their hands after a leader robot moves. Therefore, if the leader robot moves fast (rapidly pulls or pushes the carried object), some of the follower humanoid robots may lose their balance and fall down. The symmetry type cooperation discussed in this paper solves this problem because it enables all humanoid robots to move synchronously. The proposed framework is verified by dynamic simulations.     

Motion planning and contact control for a tele-assisted hydraulic underwater robot

Implementing tele-assistance or supervisory control for autonomous subsea robots requires atomic actions that can be called from high level task planners or mission managers. This paper reports on the design and implementation of a particular atomic action for the case of a subsea robot carrying out tasks in contact with the surrounding environment.Subsea vehicles equipped with manipulators can have upward of 11 degrees of freedom (DOF), with degenerate and redundant inverse kinematics. Distributed local motion planning is presented as a means to specify the motion of each robot DOF given a goal point or trajectory. Results are presented to show the effectiveness of the distributed versus non-distributed approach, a means to deal with local minima difficulties, and the performance for trajectory following with and without saturated joint angles on a robot arm.Consideration is also given to the modelling of hydraulic underwater robots and to the resulting design of hybrid position/force control strategies. A model for a hydraulically actuated robot is developed, taking into account the electrohydraulic servovalve, the bulk modulus of oil, piston area, friction, hose compliance and other arm parameters. Open and closed-loop control results are reported for simulated and real systems.Finally, the use of distributed motion planning and sequential position/force control of a Slingsby TA-9 hydraulic underwater manipulator is described, to implement an atomic action for tele-assistance. The specific task of automatically positioning and inserting a Tronic subsea mateable connector is illustrated, with results showing the contact conditions during insertion.     

Cooperative Control of a 3D Dual-Flexible-Arm Robot

This paper discusses cooperative control of a dual-flexible-arm robot to handle a rigid object in three-dimensional space. The proposed control scheme integrates hybrid position/force control and vibration suppression control. To derive the control scheme, kinematics and dynamics of the robot when it forms a closed kinematic chain is discussed. Kinematics is described using workspace force, velocity and position vectors, and hybrid position/force control is extended from that on dual-rigid-arm robots. Dynamics is derived from constraint conditions and the lumped-mass-spring model of the flexible robots and an object. The vibration suppression control is calculated from the deflections of the flexible links and the dynamics. Experiments on cooperative control are performed. The absolute positions/orientations and internal forces/moments are controlled using the robot, each arm of which has two flexible links, seven joints and a force/torque sensor. The results illustrate that the robot handled the rigid object damping links' vibration successfully in three-dimensional space.     

Neural Network Force Control for Industrial Robots

In this paper, we present a hierarchical force control framework consisting of a high level control system based on neural network and the existing motion control system of a manipulator in the low level. Inputs of the neural network are the contact force error and estimated stiffness of the contacted environment. The output of the neural network is the position command for the position controller of industrial robots. A MITSUBISHI MELFA RV-M1 industrial robot equipped with a BL Force/Torque sensor is utilized for implementing the hierarchical neural network force control system. Successful experiments for various contact motions are carried out. Additionally, the proposed neural network force controller together with the master/slave control method are used in dual-industrial robot systems. Successful experiments are carried out for the dual-robot system handling an object.     

机器人力／位置自适应模糊控制

在机器人力／位置混合控制的基础上，本文提出了一种对力控制回路采用自适应模糊控制的方法，有利于提高系统对机器人末端操纵器五外界工作环境接触时，其接触刚度不确定性的自适应能力，仿真结果表明，该控制方法与常规ＰＩＤ控制相比，系统的自适应能力和鲁棒性有显著的改善。     

Balancing of humanoid robot using contact force/moment control by task-oriented whole body control framework

Balancing control of humanoid robots is of great importance since it is a necessary functionality not only for maintaining a certain position without falling, but also for walking and running. For position controlled robots, the for-ce/torque sensors at each foot are utilized to measure the contact forces and moments, and these values are used to compute the joint angles to be commanded for balancing. The proposed approach in this paper is to maintain balance of torque-controlled robots by controlling contact force and moment using whole-body control framework with hierarchical structure. The control of contact force and moment is achieved by exploiting the full dynamics of the robot and the null-space motion in this control framework. This control approach enables compliant balancing behavior. In addition, in the case of double support phase, required contact force and moment are controlled using the redundancy in the contact force and moment space. These algorithms are implemented on a humanoid legged robot and the experimental results demonstrate the effectiveness of them.     

A Study on Kinematics and Workspace Determination of a General 6-<Emphasis Type="Underline">P</Emphasis> US Robot

This paper proposes the novel adaptive neural network (ADNN) compliant force/position control algorithm applied to a highly nonlinear serial pneumatic artificial muscle (PAM) robot as to improve its compliant force/position output performance. Based on the new adaptive neural ADNN model which is dynamically identified to adapt well all nonlinear features of the 2-axes serial PAM robot, a new hybrid adaptive neural ADNN-PID controller was initiatively implemented for compliant force/position controlling the serial PAM robot system used as an elbow and wrist rehabilitation robot which is subjected to not only the internal coupled-effects interactions but also the external end-effecter contact force variations (from 10[N] up to critical value 30[N]). The experiment results have proved the feasibility of the new control approach compared with the optimal PID control approach. The novel proposed hybrid adaptive neural ADNN-PID compliant force/position controller successfully guides the upper limb of subject to follow the linear and circular trajectories under different variable end-effecter contact force levels.     

An output feedback parallel force/position regulator for a robot manipulator in contact with a compliant environment

In this paper the problem of regulating force and position for a robot manipulator in contact with an elastically compliant environment is considered. In the framework of parallel force/position control, an output feedback regulator with gravity compensation and desired force feedforward is proposed which only requires measurements of force and position. Semiglobal stability of the closed-loop system around the equilibrium is shown via a Lyapunov argument.     

基于变刚度自适应导纳机制的机械臂恒力控制

工业机械臂在诸如打磨抛光等接触式作业任务中对环境刚度信息存在一定的依赖性, 未知环境刚度信息将严重影响机器人的力位控制精度, 使得作业效果难以得到保证. 为解决环境信息不足或未知情况下的力/位置精确控制问题, 本文首先提出了一种新的自适应环境刚度在线估计方法, 针对时变的环境刚度进行实时估计, 由此预测生成后继的机械臂参考轨迹点, 随后提出了一种根据力跟踪误差实时调整末端工具手刚度系数的变刚度导纳恒力控制方法, 并结合李雅普诺夫稳定性理论给出了整体控制律的收敛性证明. 针对刚柔两种末端工具手和多种不同的曲面工件开展了实验研究, 并与传统PID控制方法和传统导纳控制方法进行了对比, 其结果表明本文所提出的复合控制方法可在不同工况条件下实现机器人运动过程中接触力的快速柔顺调节, 并获得4.55%以内的最优力控误差效果, 证明了本文所提出方法的有效性与可行性.     

Decoupling force and motion control in industrial robots

A theoretical approach to force control design for industrial robots involved in surface-following tasks is described in this paper, assuming an infinitely stiff environment. Independent Joint Control techniques, based on standard (PID) algorithms, are adopted for position control. Force control acts as an outer loop, by adding a bias to the position set points in the joint space. A simple model and compensation of the joint flexibility effects, that play an important role in determining the dynamic behavior of the system, are also presented, leading to a force control decoupled from motion control. Some experimental results are discussed, with reference to the industrial robot SMART.