Robust Area Coverage with Connectivity Maintenance

Abstract

Robot swarms herald the ability to solve complex tasks using a large collection of simple devices. However, engineering a robotic swarm is far from trivial, with a major hurdle being the definition of the control laws leading to the desired globally coordinated behavior. Communication is a key element for coordination and it is considered one of the current most important challenges for swarm robotics. In this paper, we study the problem of maintaining robust swarm connectivity while performing a coverage task based on the Voronoi tessellation of an area of interest. We implement our methodology in a team of eight Khepera IV robots. With the assumptions that robots have a limited sensing and communication range-and cannot rely on centralized processing-we propose a tri-objective control law that outperforms other simpler strategies (e.g. a potentialbased coverage) in terms of network connectivity, robustness to failure, and area coverage.

Collaborative Multi-Robot Search and Rescue: Planning, Coordination, Perception, and Active Vision

“…Similar works aiming at cooperative search, surveillance or tracking with multi-robot systems focus on optimizing the data paths [103] or fallible robots [104], [105]. Another recent work in area coverage with connectivity maintenance is available in [106]. A comparison of local and global methods for connectivity maintenance of multi-robot networks from Khateri et al is available in [107].…”

Swarm Relays: Distributed Self-Healing Ground-and-Air Connectivity Chains

“…Algebraic Connectivity The problem of preserving end-toend connectivity is widely discussed in recent literature [3], [4], [8]. Some works use continuous control models with algebraic connectivity [9] and implement mission-related control laws [10], considering robot failures. De Gennaro et al [11] derive a gradient-based control law from Laplacian matrices' features such as the Fiedler vector to maximize connectivity.…”

A Survey on Multi-Robot Coordination in Electromagnetic Adversarial Environment: Challenges and Techniques

“…By utilizing the knowledge of connectivity quality, we may plan and control the motion of the robots to improve specified task-oriented performance, while satisfying certain communication constraints. This kind of technique is often called communication-aware motion planning [44], [45], connectivity preserving [46], [47], or connectivity maintaining [48], [49]. In this subsection, we may use connectivity-preserving planning and control (CPPC) to represent the above concepts.…”

“…On the contrary, if the distance exceeds r, the connectivity is regarded broken [58]. Within this framework, numerous research contributions about CPPC for multi-robot systems have been proposed [48], [49], [59]- [61]. For a comprehensive overview and tutorial of adopting graph-theoretic definition of connectivity, the readers are referred to [57], [62], in which the authors also provided various approaches about CPPC ranging from convex optimization to potential fields based control methods.…”