Adaptive behavior-based control for robot navigation: A multi-robot case study

Abstract

The main focus of the work presented in this paper is to investigate the application of certain biologically-inspired control strategies in the field of autonomous mobile robots, with particular emphasis on multi-robot navigation systems. The control architecture used in this work is based on the behavior-based approach. The main argument in favor of this approach is its impressive and rapid practical success. This powerful methodology has demonstrated simplicity, parallelism, perception-action mapping and real implementation. When a group of autonomous mobile robots needs to achieve a goal operating in complex dynamic environments, such a task involves high computational complexity and a large volume of data needed for continuous monitoring of internal states and the external environment. Most autonomous mobile robots have limited capabilities in computation power or energy sources with limited capability, such as batteries. Therefore, it becomes necessary to build additional mechanisms on top of the control architecture able to efficiently allocate resources for enhancing the performance of an autonomous mobile robot. For this purpose, it is necessary to build an adaptive behavior-based control system focused on sensory adaptation. This adaptive property will assure efficient use of robot's limited sensorial and cognitive resources. The proposed adaptive behavior-based control system is then validated through simulation in a multi-robot environment with a task of prey/predator scenario.