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      Research on path planning of real-time obstacle avoidance of mechanical arm based on genetic algorithm

      1 , , 1 , 2 , 3

      The Journal of Engineering

      The Institution of Engineering and Technology

      The 2nd 2018 Asian Conference on Artificial Intelligence Technology (ACAIT 2018) (ACAIT)

      8–10 June 2018

      genetic algorithms, manipulator kinematics, mobile robots, path planning, collision avoidance, real-time obstacle avoidance, genetic algorithm, modular mechanical arm, path planning algorithm, single obstacle, multiple obstacles, mechanical arm obstacle avoidance, Denavit-Hartenberg method, GA

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          Abstract

          Aiming at the problem that modular mechanical arm may collide with the obstacles in working space at runtime, a path planning algorithm of obstacle avoidance is proposed based on a genetic algorithm (GA). Firstly, the Denavit–Hartenberg method is applied to the modelling of the mechanical arm; then, the kinematic and kinetic analysis is conducted and the kinematic and kinetic equations of the mechanical arm are established. On this basis, the time, spatial distance and path length of the motion are regarded as optimising indices and the optimisation of path planning of obstacle avoidance is achieved using GA for mechanical arm under a working condition with single obstacle or multiple obstacles. Through simulation, the effectiveness and feasibility of a path planning algorithm of mechanical arm obstacle avoidance based on GA is verified. This algorithm improves the efficiency of a mechanical arm to avoid the obstacles in working space at runtime.

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          Most cited references 5

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          Obstacle avoidance of redundant manipulators using neural networks based reinforcement learning

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            Real-time collision avoidance algorithm for robotic manipulators

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              • Abstract: not found
              • Article: not found

              Wireless sensor networks: a survey

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                Author and article information

                Contributors
                Conference
                JOE
                The Journal of Engineering
                J. Eng.
                The Institution of Engineering and Technology
                2051-3305
                16 August 2018
                25 September 2018
                November 2018
                : 2018
                : 16
                : 1579-1586
                Affiliations
                [1 ] Mechanical Engineering College of Xiangtan University , Xiangtan, Hunan, People's Republic of China
                [2 ] Information Engineering College of Xiangtan University , Xiangtan, Hunan, People's Republic of China
                [3 ] Key Laboratory of Intelligent Computing and Information Processing (Xiangtan University) Ministry of Education , Xiangtan, Hunan, People's Republic of China
                Article
                JOE.2018.8266 JOE.2018.8266.R1
                10.1049/joe.2018.8266

                This is an open access article published by the IET under the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/)

                The 2nd 2018 Asian Conference on Artificial Intelligence Technology (ACAIT 2018)
                ACAIT
                2
                Chongqing University of Technology, China
                8–10 June 2018
                Page count
                Pages: 0
                Product
                Categories
                ee-cer
                cn-ait-2018
                The 2nd 2018 Asian Conference on Artificial Intelligence Technology (ACAIT 2018)

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