[Paper Review] Decentralized Autonomous Navigation Strategies for Multi-Robot Search and Rescue

Ahmad Baranzadeh|arXiv (Cornell University)|May 13, 2016

Optimization and Search Problems4 citations

TL;DR

This paper proposes three decentralized, triangular grid-based search algorithms for multi-robot search and rescue that guarantee complete coverage of unknown, obstacle-strewn environments with asymptotically optimal robot counts. Using a shared topological map and mathematically proven convergence to probability 1, the algorithms ensure efficient, collision-free exploration and target detection, validated via simulation and real-world experiments with Pioneer 3DX robots, outperforming existing methods in search time and coverage completeness.

ABSTRACT

In this report, we try to improve the performance of existing approaches for search operations in multi-robot context. We propose three novel algorithms that are using a triangular grid pattern, i.e., robots certainly go through the vertices of a triangular grid during the search procedure. The main advantage of using a triangular grid pattern is that it is asymptotically optimal in terms of the minimum number of robots required for the complete coverage of an arbitrary bounded area. We use a new topological map which is made and shared by robots during the search operation. We consider an area that is unknown to the robots a priori with an arbitrary shape, containing some obstacles. Unlike many current heuristic algorithms, we give mathematically proofs of convergence of the algorithms. The computer simulation results for the proposed algorithms are presented using a simulator of real robots and environment. We evaluate the performance of the algorithms via experiments with real robots. We compare the performance of our own algorithms with three existing algorithms from other researchers. The results demonstrate the merits of our proposed solution. A further study on formation building with obstacle avoidance for a team of mobile robots is presented in this report. We propose a decentralized formation building with obstacle avoidance algorithm for a group of mobile robots to move in a defined geometric configuration. Furthermore, we consider a more complicated formation problem with a group of anonymous robots; these robots are not aware of their position in the final configuration and need to reach a consensus during the formation process. We propose a randomized algorithm for the anonymous robots that achieves the convergence to a desired configuration with probability 1. We also propose a novel obstacle avoidance rule, used in the formation building algorithm.

Motivation & Objective

• Address the challenge of efficient, complete coverage in unknown, obstacle-filled environments using multi-robot systems.
• Overcome limitations of heuristic, centralized, or non-convergent approaches in multi-robot search and rescue.
• Develop decentralized algorithms with rigorous mathematical convergence guarantees (probability 1) for both search and formation control.
• Enable robust formation building with obstacle avoidance for anonymous robots that lack positional awareness.
• Validate performance through simulation and real-world experiments with Pioneer 3DX robots, comparing favorably to existing methods.

Proposed method

• Employ a triangular grid pattern to ensure asymptotically optimal robot deployment and complete coverage of arbitrary bounded areas.
• Implement a shared topological map built and updated dynamically by robots during search operations to track visited vertices and obstacles.
• Design three search algorithms: (1) fully random, (2) semi-random (prioritizing unvisited neighbors), and (3) modified (moving to nearest unvisited vertex anywhere).
• Use a randomized consensus algorithm for anonymous robots to achieve desired geometric formation through local interactions and convergence with probability 1.
• Integrate a novel obstacle avoidance rule into formation control that maintains formation integrity while navigating around obstacles.
• Apply rigorous mathematical proofs to establish almost-sure convergence (probability 1) for all proposed algorithms, ensuring reliability.

Experimental results

Research questions

• RQ1 Can decentralized multi-robot search algorithms achieve complete coverage of an unknown, bounded, obstacle-filled area with minimal robot count?
• RQ2 How can decentralized search be made more efficient than existing heuristic approaches while guaranteeing convergence with probability 1?
• RQ3 Can a decentralized formation control strategy maintain geometric configuration and avoid obstacles without centralized coordination?
• RQ4 How can anonymous robots (without positional knowledge) autonomously form a desired configuration through local interactions?
• RQ5 To what extent do the proposed algorithms outperform existing methods in real-world multi-robot search and formation tasks?

Key findings

• The triangular grid-based search strategy guarantees complete coverage of any bounded area with the minimum number of robots, achieving asymptotic optimality.
• All proposed search algorithms converge to complete coverage with probability 1, supported by rigorous mathematical proofs.
• Simulation results show the modified triangular-grid algorithm outperforms existing methods in search time and coverage efficiency.
• Real-world experiments with Pioneer 3DX robots confirm the feasibility and robustness of the proposed algorithms in practical environments.
• The formation control algorithm with obstacle avoidance successfully achieves desired configurations with anonymous robots, converging with probability 1.
• The proposed obstacle avoidance rule effectively maintains formation integrity during navigation, validated through simulation and theoretical analysis.