Different Nature-Inspired Techniques Applied for Motion Planning of Wheeled Robot: A Critical Review

Kashyap, Abhishek; Pandey, Anish

doi:10.15226/2473-3032/3/2/00136

Cited by 18 publications

(2 citation statements)

References 75 publications

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“…Mobile robot control has been widely used in automated navigation system. The aim of the automated navigation is to guide the robot or vehicle moving between obstacles to reach the target from the start point with collision-free performance (Kashyap and Pandey, 2018;Patle et al, 2019). During the navigation control, observations are made by the sensors and actuators equipped on a real robot or vehicle; the input signal is noisy and uncertain.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Multirobot Navigation and Arrival-Time Control Using a Scalable PSO-Optimized Hierarchical Controller

Chang¹,

Dostovalova²,

Lin³

et al. 2020

Front. Artif. Intell.

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We present a hierarchical fuzzy logic system for precision coordination of multiple mobile agents such that they achieve simultaneous arrival at their destination positions in a cluttered urban environment. We assume that each agent is equipped with a 2D scanning Lidar to make movement decisions based on local distance and bearing information. Two solution approaches are considered and compared. Both of them are structured around a hierarchical arrangement of control modules to enable synchronization of the agents' arrival times while avoiding collision with obstacles. The proposed control module controls both moving speeds and directions of the robots to achieve the simultaneous target-reaching task. The control system consists of two levels: the lower-level individual navigation control for obstacle avoidance and the higher-level coordination control to ensure the same time of arrival for all robots at their target. The first approach is based on cascading fuzzy logic controllers, and the second approach considers the use of a Long Short-Term Memory recurrent neural network module alongside fuzzy logic controllers. The parameters of all the controllers are optimized using the particle swarm optimization algorithm. To increase the scalability of the proposed control modules, an interpolation method is introduced to determine the velocity scaling factors and the searching directions of the robots. A physics-based simulator, Webots, is used as a training and testing environment for the two learning models to facilitate the deployment of codes to hardware, which will be conducted in the next phase of our research.

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Section: Introductionmentioning

confidence: 99%

Intelligent Multirobot Navigation and Arrival-Time Control Using a Scalable PSO-Optimized Hierarchical Controller

Chang¹,

Dostovalova²,

Lin³

et al. 2020

Front. Artif. Intell.

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“…The simulation results were favourable, but the actual experimental results were not given. In [5], the research on motion planning of wheeled robots with various heuristic techniques was summarized in the past twenty years, and the solutions to key problems were shared. However, it was difficult for these methods to find the optimal solution due to the large amount of calculation.…”

Section: Introductionmentioning

confidence: 99%

Research on Local Dynamic Path Planning Method for Intelligent Vehicle Lane-Changing

Liu

Zhang

Wang

2019

Journal of Advanced Transportation

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A local dynamic path planning method is proposed to compensate for the lack of consideration of the movement state of surrounding vehicles, the poor comfort, and the low traffic efficiency when the existing vehicle changes lanes automatically. Firstly, the cubic polynomial is predefined, and the optimal track path is solved. According to the real-time information of environment perception, the model is continuously modified by acquiring real-time information in the course of path planning, and the regional safety of the vehicle is realized. The Carsim and simulink simulation results and actual vehicle verification show that, compared with the traditional nondynamic research method, this method can effectively solve the problem that the vehicle speed variation and the sudden intrusions of the vehicle leading to the compulsory operation of the vehicle during the course of lane-changing. The safety is also improved. In order to ensure the vehicle comfort and stability, the lane-changing time is shortened by 20%, and the efficiency of lane-changing is improved obviously.

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Hybrid Approach based on Multi‐agent System and Fuzzy Logic for Mobile Robot Autonomous Navigation

Yahyaoui

2022

Optimization and Machine Learning

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Different Nature-Inspired Techniques Applied for Motion Planning of Wheeled Robot: A Critical Review

Cited by 18 publications

References 75 publications

Intelligent Multirobot Navigation and Arrival-Time Control Using a Scalable PSO-Optimized Hierarchical Controller

Intelligent Multirobot Navigation and Arrival-Time Control Using a Scalable PSO-Optimized Hierarchical Controller

Research on Local Dynamic Path Planning Method for Intelligent Vehicle Lane-Changing

Hybrid Approach based on Multi‐agent System and Fuzzy Logic for Mobile Robot Autonomous Navigation

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