A Behavior-Based Strategy for Single and Multi-Robot Autonomous Exploration

Abstract

In this paper, we consider the problem of autonomous exploration of unknown environments with single and multiple robots. This is a challenging task, with several potential applications. We propose a simple yet effective approach that combines a behavior-based navigation with an efficient data structure to store previously visited regions. This allows robots to safely navigate, disperse and efficiently explore the environment. A series of experiments performed using a realistic robotic simulator and a real testbed scenario demonstrate that our technique effectively distributes the robots over the environment and allows them to quickly accomplish their mission in large open spaces, narrow cluttered environments, dead-end corridors, as well as rooms with minimum exits.

Leveraging area bounds information for autonomous decentralized multi-robot exploration

“…Similar approaches include that of Lau [10], Julia et al [12], Renzaglia [13], Baxter [14], Cepeda [15] and Popa [16]. Baxter [14] presents a potential field approach in which the field is shared among robots.…”

“…Baxter [14] presents a potential field approach in which the field is shared among robots. Cepeda [15] proposed a behavior based approach for multi-robot exploration, but such an approach has difficulty in robot exploration status synchronization. Popa [16] uses potential fields for dispersion of sensor networks, but does not discuss exploration or path-planning.…”

A Cognitive Agent-based Model for Multi-Robot Coverage at a City Scale

“…However, such concise algorithmic approaches are not suitable for unstructured and dynamic environments (Cepeda et al 2012), such as cities. The city-scale multi-robot coverage have many potential applications, such as sweeping (garbage-collection, mine sweeping, pesticide and water spray etc.…”

“…The motivation of our mechanism is from Cepeda et al (2012), in which, a behavior based strategy of multi-robot exploration is presented. The authors have introduced four behaviors, named as "exploration", "dispersion", "obstacle avoidance", and "avoiding past".…”

“…In the mechanism presented in this paper, we have generalized the robot's behavior [presented in Cepeda et al (2012)] into an agent's behavior, and extended the model in such a way that it has more explicit representation of space and sensed parameters. Hence, our model can be used with any of the agent modeling simulator which has a space representation in cellular automata.…”