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Abstract
This paper discusses the importance, the complexity and the challenges of mapping mobile robot's unknown and dynamic environment, besides the role of sensors and the problems inherited in map building. These issues remain largely an open research problems in developing dynamic navigation systems for mobile robots. The paper presenst the state of the art in map building and localization for mobile robots navigating within unknown environment, and then introduces a solution for the complex problem of autonomous map building and maintenance method with focus on developing an incremental grid based mapping technique that is suitable for real-time obstacle detection and avoidance. In this case, the navigation of mobile robots can be treated as a problem of tracking geometric features that occur naturally in the environment of the robot. The robot maps its environment incrementally using the concept of occupancy grids and the fusion of multiple ultrasonic sensory information while wandering in it and stay away from all obstacles. To ensure real-time operation with limited resources, as well as to promote extensibility, the mapping and obstacle avoidance modules are deployed in parallel and distributed framework. Simulation based experiments has been conducted and illustrated to show the validity of the developed mapping and obstacle avoidance approach.
Highlights
An autonomous mobile robot is required to wander around and explore its environment without colliding with any obstacles for the purpose to fill its mission by executing successfully an assigned task, and to survive by affording the possibility of finding energy sources and avoid dangerous hazards
Building maps of unknown and dynamic environment is an essential probem in robotics and requires taking care of connected problems other than mapping itself, such as localization, sensor uncertainty, obstacle avoidance and real-time navigation
The generalized Voronoi graph (GVG) serves as a high-level topological map organizing a collection of feature-based maps at the lower level, and this leads to create a hierarchical approach to the simultaneous localization and mapping (Lisien et al, 2003)
Summary
An autonomous mobile robot is required to wander around and explore its environment without colliding with any obstacles for the purpose to fill its mission by executing successfully an assigned task, and to survive by affording the possibility of finding energy sources and avoid dangerous hazards. Building maps of unknown and dynamic environment is an essential probem in robotics and requires taking care of connected problems other than mapping itself, such as localization, sensor uncertainty, obstacle avoidance and real-time navigation. Vision systems are passive and of high resolution but it demands high computation Ultrasonic range finders are common in mobile robot navigation due to their simplicity of operation, high working speed and cheap but usually they are very crude These sensors provide relative distances between them and surrounding obstacles/objects located within their radiation cone. This paper discusses the importance, the complexity and the challenges of mapping robot’s unknown and dynamic environment, besides the role of sensors and the problems inherited in map building These issues remain largely an open research problem in developing an autonomous navigation system for mobile robots. Simulation based experiments has been conducted and illustrated to show the validity of the developed mapping and obstacle avoidance approach
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