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An Improved Timed Elastic Band (TEB) Algorithm of Autonomous Ground Vehicle (AGV) in Complex Environment
by
Wu, Jiafeng
, Ma, Xianghua
, Peng, Tongrui
, Wang, Haojie
in
AGV
/ Communication
/ Genetic algorithms
/ Heuristic
/ Kinematics
/ local path planning
/ Optimization
/ Robots
/ Sparsity
/ TEB algorithm
/ the shortest distance constraint
2021
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An Improved Timed Elastic Band (TEB) Algorithm of Autonomous Ground Vehicle (AGV) in Complex Environment
by
Wu, Jiafeng
, Ma, Xianghua
, Peng, Tongrui
, Wang, Haojie
in
AGV
/ Communication
/ Genetic algorithms
/ Heuristic
/ Kinematics
/ local path planning
/ Optimization
/ Robots
/ Sparsity
/ TEB algorithm
/ the shortest distance constraint
2021
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Do you wish to request the book?
An Improved Timed Elastic Band (TEB) Algorithm of Autonomous Ground Vehicle (AGV) in Complex Environment
by
Wu, Jiafeng
, Ma, Xianghua
, Peng, Tongrui
, Wang, Haojie
in
AGV
/ Communication
/ Genetic algorithms
/ Heuristic
/ Kinematics
/ local path planning
/ Optimization
/ Robots
/ Sparsity
/ TEB algorithm
/ the shortest distance constraint
2021
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An Improved Timed Elastic Band (TEB) Algorithm of Autonomous Ground Vehicle (AGV) in Complex Environment
Journal Article
An Improved Timed Elastic Band (TEB) Algorithm of Autonomous Ground Vehicle (AGV) in Complex Environment
2021
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Overview
In recent decades, the Timed Elastic Band (TEB) algorithm is widely used for the AGV local path panning because of its convenient and efficiency. However, it may make a local detour when encountering a curve turn and cause excessive energy consumption. To solve this problem, this paper proposed an improved TEB algorithm to make the AGV walk along the wall when turning, which shortens the planning time and saves energy. Experiments were implemented in the Rviz visualization tool platform of the robot operating system (ROS). Simulated experiment results reflect that an amount of 5% reduction in the planning time has been achieved and the velocity curve implies that the operation was relatively smooth. Practical experiment results demonstrate the effectiveness and feasibility of the proposed method that the robots can avoid obstacles smoothly in the unknown static and dynamic obstacle environment.
Publisher
MDPI AG,MDPI
Subject
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