2012•Proceedings of Sustainable Research and Innovation ConferenceRequires access

Obstacle Avoidance and Path Planning Schemes for Autonomous Navigation of a Mobile Robot: A Review

J. A. Oroko, George Nyauma Nyakoe

Open publisher page 45 citations

Abstract

Autonomous navigation of a mobile robot involves self-steering of a robot from one place to another based on computational resources on-board the robot. There are many different ways to approach mobile robot navigation, with path planning and obstacle avoidance playing a key role. This paper discusses three methods used in obstacle avoidance and path planning i.e., the Bug algorithms, the Potential Field methods and the Vector Field Histogram method which are all active sensor-based methods. A more robust system for use to achieve autonomous navigation in any environment can be developed by fusing technologies or schemes by taking advantage of the merits of the different systems while limiting their drawbacks.

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What this paper is about

Autonomous navigation of a mobile robot involves self-steering of a robot from one place to another based on computational resources on-board the robot. There are many different ways to approach mobile robot navigation, with path planning and obstacle avoidance playing a key role. This paper discusses three methods used in obstacle avoidance and path planning i.e., the Bug algorithms, the Potential Field methods and the Vector Field Histogram method which are all active sensor-based methods. A more robust system for use to achieve autonomous navigation in any environment can be developed by fusing technologies or schemes by taking advantage of the merits of the different systems while limiting their drawbacks.

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OpenAlex reports 45 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Autonomous navigation of a mobile robot involves self-steering of a robot from one place to another based on computational resources on-board the robot. There are many different ways to approach mobile robot navigation, with path planning and obstacle avoidance playing a key role. This paper discusses three methods used in obstacle avoidance and path planning i.e., the Bug algorithms, the Potential Field methods and the Vector Field Histogram method which are all active sensor-based methods. A more robust system for use to achieve autonomous navigation in any environment can be developed by fusing technologies or schemes by taking advantage of the merits of the different systems while limiting their drawbacks.

Key concepts: Obstacle avoidance, Mobile robot, Mobile robot navigation, Motion planning, Obstacle, Key (lock), Computer science, Collision avoidance

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