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Open AccessJournal ArticleDOI

Mobile Robot Navigation and Obstacle Avoidance Techniques: A Review

Anish P, +3 more
- Vol. 2, Iss: 3
TLDR
The present article focuses on the study of the intelligent navigation techniques, which are capable of navigating a mobile robot autonomously in static as well as dynamic environments.
Abstract
Mobile robot is an autonomous agent capable of navigating intelligently anywhere using sensor actuator control techniques The applications of the autonomous mobile robot in many fields such as industry space defence and transportation and other social sectors are growing day by day The mobile robot performs many tasks such as rescue operation patrolling disaster relief planetary exploration and material handling etc Therefore an intelligent mobile robot is required that could travel autonomously in various static and dynamic environments Several techniques have been applied by the various researchers for mobile robot navigation and obstacle avoidance The present article focuses on the study of the intelligent navigation techniques which are capable of navigating a mobile robot autonomously in static as well as dynamic environments

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Journal ArticleDOI

A Review on Challenges of Autonomous Mobile Robot and Sensor Fusion Methods

TL;DR: A comprehensive study on devices/sensors and prevalent sensor fusion techniques developed for tackling issues like localization, estimation and navigation in mobile robot are presented and give good direction for further investigation on developing methods to deal with the discrepancies faced with autonomous mobile robot.
Journal ArticleDOI

Deep reinforcement learning based mobile robot navigation: A review

TL;DR: This paper systematically compares and analyzes the relationship and differences between four typical application scenarios: local obstacle avoidance, indoor navigation, multi-robot navigation, and social navigation; and describes the development of DRL-based navigation.
Journal ArticleDOI

A Survey of Machine Learning Techniques for Indoor Localization and Navigation Systems

TL;DR: In this paper, a comprehensive state-of-the-art survey on machine learning techniques that have recently been adopted for indoor localization purposes is presented, along with basic localization principles, applications, and the underlying problems and challenges associated with the existing systems.
Journal ArticleDOI

Toward Socially Aware Person-Following Robots

TL;DR: To guide the design of socially aware person following robots, a user-needs layered design framework that combines the four factor categories is proposed and provides a systematic way to incorporate social considerations in theDesign of person-following robots.
Journal ArticleDOI

Mobile robot path planning in dynamic environment based on cuckoo optimization algorithm

TL;DR: A new method based on cuckoo optimization algorithm is proposed for solving the mobile robot path planning problem in a dynamic environment and the feature vector is reduced in dimension via a new proposed technique to diminish the computational complexity.
References
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Motion planning in a plane using generalized Voronoi diagrams

TL;DR: An algorithm for planning a collision-free path for a rectangle in a planar workspace populated with polygonal obstacles is presented and is demonstrated to be quite fast with execution times comparable to, or exceeding, those of the freeway method.
Journal ArticleDOI

Path planning for autonomous mobile robot navigation with ant colony optimization and fuzzy cost function evaluation

TL;DR: A novel proposal to solve the problem of path planning for mobile robots based on Simple Ant Colony Optimization Meta-Heuristic (SACO-MH), named SACOdm, where d stands for distance and m for memory.
Journal ArticleDOI

Robot path planning in uncertain environment using multi-objective particle swarm optimization

TL;DR: Several new operations/improvements such as the particle update method based on random sampling and uniform mutation, the infeasible archive, the constrained domination relationship based on collision times with obstacles, are incorporated into the proposed algorithm to improve its effectiveness.
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