A biologically inspired controller to solve the coverage problem in robotics

Area of Science:

• Robotics
• Computational Geometry
• Biologically Inspired Systems

Background:

• The coverage problem requires robots to traverse all points in an area, with applications in cleaning and demining.
• Existing solutions use planning or heuristic methods, requiring theoretical or experimental validation.
• Novel approaches are needed for efficient and adaptable coverage strategies.

Purpose of the Study:

• To present a novel solution to the robot coverage problem.
• To exploit the chaotic behavior of a Braitenberg vehicle 2b for area coverage.
• To reduce environmental assumptions and enable on-board sensor implementation.

Main Methods:

• Theoretical analysis of the Braitenberg vehicle 2b's motion equations.
• Reduction of motion equations to a Hamiltonian system.
• Extensive simulations to validate coverage in bounded workspaces.

Main Results:

• The Braitenberg vehicle 2b exhibits quasi-periodic or chaotic trajectories, theoretically solving the coverage problem.
• Simulations demonstrate effective coverage of bounded regions.
• Full coverage is achieved with a short perceptual range.

Conclusions:

• The Braitenberg vehicle 2b offers a theoretically sound and practically viable solution for the robot coverage problem.
• This chaotic motion approach is less restrictive than previous methods.
• The method is suitable for implementation with on-board sensors.