Learning Forward Models for the Operational Space Control of Redundant Robots

A whole resolved motion rate control algorithm designed for mobile dual-arm redundant robots is presented in this article. Based on this algorithm, the end-effector movements of the dual arms of the mobile dual-arm redundant robot can be decomposed into the movements of the two driving wheels of the differential driving platform and the movements of the dual-arm each joint of this robot harmoniously. The influence of the redundancies of the single- and dual-arm robots on the operation based on the fixed- and differential-driving platforms, which are then based on the whole resolved motion rate control algorithm, is studied after building their motion models. Some comparisons are made to show the advantages of this algorithm on the entire modeling of the complicated robotic system and the influences of the redundancy. First, the comparison of the simulation results between the fixed single-arm robot and the mobile single-arm robot is presented. Second, a comparison of the simulation results between the mobile single-arm robot and the mobile dual-arm robots is shown. Compared with the mobile single-arm robot and the fixed dual-arm robot based on this algorithm, the mobile dual-arm robot has more redundancy and can simultaneously track and operate different objects. Moreover, the mobile dual-arm redundant robot has better smoothness, more flexibility, larger operational space, and more harmonious cooperation between the two arms and the differential driving platform during the entire mobile operational process.

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Control of redundant robots using learned models: An operational space control approach

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems ◽

10.1109/iros.2009.5354438 ◽

2009 ◽

Cited By ~ 11

Author(s):

Camille Salaun ◽

Vincent Padois ◽

Olivier Sigaud

Keyword(s):

Control Approach ◽

Redundant Robots ◽

Operational Space

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Forward Models for Following a Moving Target with the Puma 560 Robot Manipulator

INTELIGENCIA ARTIFICIAL ◽

10.4114/intartif.vol18iss56pp31-42 ◽

2015 ◽

Vol 18 (56) ◽

pp. 31

Author(s):

Daniel Fernando Tello Gamarra ◽

Marco Antonio De Souza Leite Cuadros

Keyword(s):

Neural Networks ◽

Robot Manipulator ◽

Forward Model ◽

Control Architecture ◽

Moving Target ◽

Rbf Neural Networks ◽

Forward Models ◽

Operational Space ◽

Manipulator Robot

This paper describes how a forward model could be applied in a manipulator robot to accomplish the task of following a moving target. The forward model has been implemented in the puma 560 robot manipulator in simulation after a babbling motor phase using ANFIS neural networks. The forward model delivers a rough estimation of the position in the operational space of a moving target. Using this information a Cartesian controller tracks the moving target. An implementation of the proposed architecture and the Piepmeir algorithm for the problem of following a moving target is also shown in the paper. The control architecture proposed in this paper was also tested with MLP and RBF neural networks. Results and simulations are shown to demonstrate the applicability of our proposed architecture for tracking a moving target.

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ControlIt! — A Software Framework for Whole-Body Operational Space Control

International Journal of Humanoid Robotics ◽

10.1142/s0219843615500401 ◽

2016 ◽

Vol 13 (01) ◽

pp. 1550040 ◽

Cited By ~ 9

Author(s):

Chien-Liang Fok ◽

Gwendolyn Johnson ◽

John D. Yamokoski ◽

Aloysius Mok ◽

Luis Sentis

Keyword(s):

Upper Body ◽

Whole Body ◽

Software Framework ◽

Physical Constraints ◽

Lower Priority ◽

Redundant Robots ◽

Operational Space ◽

Floating Base ◽

Position Task ◽

Product Disassembly

Whole Body Operational Space Control (WBOSC) enables floating-base highly redundant robots to achieve unified motion/force control of one or more operational space objectives while adhering to physical constraints. It is a pioneering algorithm in the field of human-centered Whole-Body Control (WBC). Although there are extensive studies on the algorithms and theory behind WBOSC, limited studies exist on the software architecture and APIs that enable WBOSC to perform and be integrated into a larger system. In this paper, we address this by presenting ControlIt!, a new open-source software framework for WBOSC. Unlike previous implementations, ControlIt! is multi-threaded to increase maximum servo frequencies using standard PC hardware. A new parameter binding mechanism enables tight integration between ControlIt! and external processes via an extensible set of transport protocols. To support a new robot, only two plugins and a URDF model is needed — the rest of ControlIt! remains unchanged. New WBC primitives can be added by writing Task or Constraint plugins. ControlIt!’s capabilities are demonstrated on Dreamer, a 16-DOF torque controlled humanoid upper body robot containing both series elastic and co-actuated joints, and using it to perform a product disassembly task. Using this testbed, we show that ControlIt! can achieve average servo latencies of about 0.5[Formula: see text]ms when configured with two Cartesian position tasks, two orientation tasks, and a lower priority posture task. This is 10 times faster than the 5[Formula: see text]ms that was achieved using UTA-WBC, the prototype implementation of WBOSC that is both application and platform-specific. Variations in the product’s position is handled by updating the goal of the Cartesian position task. ControlIt!’s source code is released under LGPL and we hope it will be adopted and maintained by the WBC community for the long term as a platform for WBC development and integration.

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Comparison of null-space and minimal null-space control algorithms

Robotica ◽

10.1017/s0263574707003402 ◽

2007 ◽

Vol 25 (5) ◽

pp. 511-520 ◽

Cited By ~ 15

Author(s):

Bojan Nemec ◽

Leon Žlajpah ◽

Damir Omrčen

Keyword(s):

Degrees Of Freedom ◽

Null Space ◽

Space Velocity ◽

Control Algorithms ◽

Robot Arm ◽

Velocity Control ◽

Redundant Robots ◽

Operational Space ◽

Space Projection ◽

The Stability

SUMMARYThis paper deals with the stability of null-space velocity control algorithms in extended operational space for redundant robots. We compare the performance of the control algorithm based on the minimal null-space projection and generalized-inverse-based projection into the Jacobian null-space. We show how the null-space projection affects the performance of the null-space tracking algorithm. The results are verified with the simulation and real implementation on a redundant mobile robot composed of 3 degrees of freedom (DOFs) mobile platform and 7-DOF robot arm.

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Shape Sensing of Hyper-Redundant Robots Using an AHRS IMU Sensor Network

Sensors ◽

10.3390/s22010373 ◽

2022 ◽

Vol 22 (1) ◽

pp. 373

Author(s):

Ciprian Lapusan ◽

Olimpiu Hancu ◽

Ciprian Rad

Keyword(s):

Sensor Network ◽

Kinematic Model ◽

Sensory System ◽

Feedback System ◽

Computational Time ◽

Redundant Robots ◽

Testing Method ◽

Operational Space ◽

Novel Approach ◽

Shape Sensing

The paper proposes a novel approach for shape sensing of hyper-redundant robots based on an AHRS IMU sensor network embedded into the structure of the robot. The proposed approach uses the data from the sensor network to directly calculate the kinematic parameters of the robot in modules operational space reducing thus the computational time and facilitating implementation of advanced real-time feedback system for shape sensing. In the paper the method is applied for shape sensing and pose estimation of an articulated joint-based hyper-redundant robot with identical 2-DoF modules serially connected. Using a testing method based on HIL techniques the authors validate the computed kinematic model and the computed shape of the robot prototype. A second testing method is used to validate the end effector pose using an external sensory system. The experimental results obtained demonstrate the feasibility of using this type of sensor network and the effectiveness of the proposed shape sensing approach for hyper-redundant robots.

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