Singularity robustness: methods for joint-space and task-space control

2002 ◽  
Author(s):  
K. Wedeward ◽  
R. Colbaugh ◽  
A. Engelmann
Keyword(s):  
Joint Space ◽  
Task Space ◽  
Task Space Control ◽  
And Task

scholarly journals A Berry Picking Robot With A Hybrid Soft-Rigid Arm: Design and Task Space Control

2020 ◽  
Author(s):  
Naveen Kumar Uppalapati ◽  
Benjamin Walt ◽  
Aaron Havens ◽  
Armeen Mahdian ◽  
Girish Chowdhary ◽  
...  
Keyword(s):  
Task Space ◽  
Task Space Control ◽  
And Task

Task-Space Framework for Bilateral Teleoperation With Time Delays

2012 ◽  
Vol 134 (5) ◽  
Author(s):  
Hanlei Wang ◽  
Yongchun Xie
Keyword(s):  
Time Delays ◽  
Joint Space ◽  
Schwarz Inequality ◽  
Bilateral Teleoperation ◽  
Task Space ◽  
Control Approach ◽  
Energy Flows ◽  
Control Framework ◽  
Communication Time ◽  
Task Space Control

This paper investigates the task-space control framework for bilateral teleoperation with communication time delays. Teleoperation in task space R3 × SO(3) presents some distinctive features different from its joint-space counterpart, i.e., SO(3) is nonconvex and bears quite different structure from Euclidean space Rn. Through analyzing the energy flows at the two ports of the teleoperator, we rigorously define the task-space interaction passivity of the teleoperator. Based on this passivity framework, we propose delay-robust control schemes to achieve master–slave position/orientation synchronization. Singularity-free task-space interaction passivity of the closed-loop teleoperator is ensured by the proposed task-space control framework. Using Lyapunov–Krasovskii stability tool and Schwarz inequality, we analyze the performance of the proposed teleoperation control scheme. We also discuss the problems incurred by time-varying delays and the corresponding solutions. Simulation study on a master–slave teleoperator composed of two kinematically dissimilar six-degree of freedom (DOF) manipulators is performed to illustrate the performance of the proposed control approach.

Kinematic Effects of Gimbal Joints on a 3URU Parallel Manipulator

2012 ◽  
Author(s):  
Sina Baghi ◽  
Fariborz Razban ◽  
Kambiz G. Osgouie
Keyword(s):  
Parallel Manipulator ◽  
Joint Space ◽  
Task Space ◽  
Mechanical Advantage ◽  
Robotic Arms ◽  
Revolute Joints ◽  
Non Linear ◽  
And Task

Gimbal transmissions are non-linear direct transmissions and can be used in robotic arms replacing the traditional revolute joints. They offer potential advantages for critical cases such as joint space and task space singularities or where a different mechanical advantage is needed compared to what traditional revolute joints provide. This can be obtained by properly adjusting the different parameters of Gimbal joints used in different joints of the manipulator (such as their offset angle and/or chamfer angle). In this paper the concept of Gimbal mechanism as a joint is investigated. Then, as an example, Gimbal joints are used to replace the basic revolute joints of a 3-UPU parallel manipulator and actuator velocities are obtained for a task space trajectory. The outcomes for a manipulator with traditional revolute joints and with Gimbal equipped joints are compared. Then the workspace and dexterity analyses are done on both manipulators.

scholarly journals Task-space regulation of rigid-link electrically-driven robots with uncertain kinematics using neural networks

2021 ◽  
Vol 54 (1-2) ◽  
pp. 102-115
Author(s):  
Wenhui Si ◽  
Lingyan Zhao ◽  
Jianping Wei ◽  
Zhiguang Guan
Keyword(s):  
Neural Networks ◽  
Asymptotic Stability ◽  
Control Method ◽  
Joint Space ◽  
Robot Kinematics ◽  
Rbf Neural Networks ◽  
Task Space ◽  
Actuator Dynamics ◽  
Rigid Link ◽  
On Line

Extensive research efforts have been made to address the motion control of rigid-link electrically-driven (RLED) robots in literature. However, most existing results were designed in joint space and need to be converted to task space as more and more control tasks are defined in their operational space. In this work, the direct task-space regulation of RLED robots with uncertain kinematics is studied by using neural networks (NN) technique. Radial basis function (RBF) neural networks are used to estimate complicated and calibration heavy robot kinematics and dynamics. The NN weights are updated on-line through two adaptation laws without the necessity of off-line training. Compared with most existing NN-based robot control results, the novelty of the proposed method lies in that asymptotic stability of the overall system can be achieved instead of just uniformly ultimately bounded (UUB) stability. Moreover, the proposed control method can tolerate not only the actuator dynamics uncertainty but also the uncertainty in robot kinematics by adopting an adaptive Jacobian matrix. The asymptotic stability of the overall system is proven rigorously through Lyapunov analysis. Numerical studies have been carried out to verify efficiency of the proposed method.

Sign in / Sign up

Export Citation Format

Share Document