Obstacle Avoidance for Redundant Manipulators Utilizing a Backward Quadratic Search Algorithm
Obstacle avoidance can be achieved as a secondary task by appropriate inverse kinematics (IK) resolution of redundant manipulators. Most prior literature requires the time-consuming determination of the closest point to the obstacle for every calculation step. Aiming at the relief of computational b...
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Series: | International Journal of Advanced Robotic Systems |
Online Access: | https://doi.org/10.5772/63934 |
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doaj-12299de57b1e4a788f40c6c9ee89bf442020-11-25T03:24:08ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142016-06-011310.5772/6393410.5772_63934Obstacle Avoidance for Redundant Manipulators Utilizing a Backward Quadratic Search AlgorithmTianjian Hu0Tianshu Wang1Junfeng Li2Weiping Qian3 School of Aerospace Engineering, Tsinghua University, Beijing, China School of Aerospace Engineering, Tsinghua University, Beijing, China School of Aerospace Engineering, Tsinghua University, Beijing, China Beijing Institute of Tracking and Telecommunication Technology, Beijing, ChinaObstacle avoidance can be achieved as a secondary task by appropriate inverse kinematics (IK) resolution of redundant manipulators. Most prior literature requires the time-consuming determination of the closest point to the obstacle for every calculation step. Aiming at the relief of computational burden, this paper develops what is termed a backward quadratic search algorithm (BQSA) as another option for solving IK problems in obstacle avoidance. The BQSA detects possible collisions based on the root property of a category of quadratic functions, which are derived from ellipse-enveloped obstacles and the positions of each link's end-points. The algorithm executes a backward search for possible obstacle collisions, from the end-effector to the base, and avoids obstacles by utilizing a hybrid IK scheme, incorporating the damped least-squares method, the weighted least-norm method and the gradient projection method. Some details of the hybrid IK scheme, such as values of the damped factor, weights and the clamping velocity, are discussed, along with a comparison of computational load between previous methods and BQSA. Simulations of a planar seven-link manipulator and a PUMA 560 robot verify the effectiveness of BQSA.https://doi.org/10.5772/63934 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Tianjian Hu Tianshu Wang Junfeng Li Weiping Qian |
spellingShingle |
Tianjian Hu Tianshu Wang Junfeng Li Weiping Qian Obstacle Avoidance for Redundant Manipulators Utilizing a Backward Quadratic Search Algorithm International Journal of Advanced Robotic Systems |
author_facet |
Tianjian Hu Tianshu Wang Junfeng Li Weiping Qian |
author_sort |
Tianjian Hu |
title |
Obstacle Avoidance for Redundant Manipulators Utilizing a Backward Quadratic Search Algorithm |
title_short |
Obstacle Avoidance for Redundant Manipulators Utilizing a Backward Quadratic Search Algorithm |
title_full |
Obstacle Avoidance for Redundant Manipulators Utilizing a Backward Quadratic Search Algorithm |
title_fullStr |
Obstacle Avoidance for Redundant Manipulators Utilizing a Backward Quadratic Search Algorithm |
title_full_unstemmed |
Obstacle Avoidance for Redundant Manipulators Utilizing a Backward Quadratic Search Algorithm |
title_sort |
obstacle avoidance for redundant manipulators utilizing a backward quadratic search algorithm |
publisher |
SAGE Publishing |
series |
International Journal of Advanced Robotic Systems |
issn |
1729-8814 |
publishDate |
2016-06-01 |
description |
Obstacle avoidance can be achieved as a secondary task by appropriate inverse kinematics (IK) resolution of redundant manipulators. Most prior literature requires the time-consuming determination of the closest point to the obstacle for every calculation step. Aiming at the relief of computational burden, this paper develops what is termed a backward quadratic search algorithm (BQSA) as another option for solving IK problems in obstacle avoidance. The BQSA detects possible collisions based on the root property of a category of quadratic functions, which are derived from ellipse-enveloped obstacles and the positions of each link's end-points. The algorithm executes a backward search for possible obstacle collisions, from the end-effector to the base, and avoids obstacles by utilizing a hybrid IK scheme, incorporating the damped least-squares method, the weighted least-norm method and the gradient projection method. Some details of the hybrid IK scheme, such as values of the damped factor, weights and the clamping velocity, are discussed, along with a comparison of computational load between previous methods and BQSA. Simulations of a planar seven-link manipulator and a PUMA 560 robot verify the effectiveness of BQSA. |
url |
https://doi.org/10.5772/63934 |
work_keys_str_mv |
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