Navigational Control Analysis of Mobile Robot in Cluttered Unknown Environment Using Novel Neural-GSA Technique

Das, Swadhin Sambit; Mohanty, Suranjan; Behera, A. K.; Parhi, Dayal R.; Pradhan, Saroj Kr.

doi:10.1007/978-981-15-2696-1_54

Cited by 1 publication

(1 citation statement)

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“…For the same task, Alaraji et al present a brief comparative study between some optimization-based algorithms [30]. Later, Das et al in [31], present an application of thee Gravitational Search Algorithm (GSA) to the task of navigating cluttered unknown environments. With a more experimental approach Chen et al [32] show a methodology for crowd navigation based on a graph convolutional network which makes use of the gaze information of the individuals in the crowd.…”

Section: Introduction and Related Workmentioning

confidence: 99%

Crowded Environment Navigation with NEAT: Impact of Perception Resolution on Controller Optimization

Seriani

Marcini

Caruso

et al. 2021

J Intell Robot Syst

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Crowd navigation with autonomous systems is a topic which has seen a rapid increase in interest recently. While it appears natural to humans, being able to reach a target can prove difficult or impossible to a mobile robot because of the safety issues related to collisions with people. In this work we propose an approach to control a robot in a crowded environment; the method employs an Artificial Neural Network (ANN) that is trained with the NeuroEvolution of Augmented Topologies (NEAT) method. Models for the kinematics, perception, and cognition of the robot are presented. In particular, perception is based on a raycasting model which is tailored on the ANN. An in-depth analysis of a number of parameters of the environment and the robot is performed and a comparative analysis is presented; finally, results of the performance of the controller trained with NEAT are compared to those of a human driver who takes over the controller itself. Results show that the intelligent controller is able to perform on par with the human, within the simulated environment.

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Section: Introduction and Related Workmentioning

confidence: 99%