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

TLDR

Search and rescue operations can benefit from autonomous or teleoperated robots and multi‑robot systems for mapping, situational assessment, surveillance, communication, and victim search. This survey reviews multi‑robot systems for SAR, covering heterogeneous robots, active perception, and key research questions such as shared autonomy, sim‑to‑real transfer, victim awareness, coordination, and interoperability. The survey contextualizes topics within the challenges and constraints faced by ground, aerial, surface, and underwater robots across maritime, urban, wilderness, and other post‑disaster settings. It is the first survey to cover heterogeneous SAR robots across environments, active perception in multi‑robot systems, and dual perspectives from multi‑agent perception and control.

Abstract

Search and rescue (SAR) operations can take significant advantage from supporting autonomous or teleoperated robots and multi-robot systems. These can aid in mapping and situational assessment, monitoring and surveillance, establishing communication networks, or searching for victims. This paper provides a review of multi-robot systems supporting SAR operations, with system-level considerations and focusing on the algorithmic perspectives for multi-robot coordination and perception. This is, to the best of our knowledge, the first survey paper to cover (i) heterogeneous SAR robots in different environments, (ii) active perception in multi-robot systems, while (iii) giving two complementary points of view from the multi-agent perception and control perspectives. We also discuss the most significant open research questions: shared autonomy, sim-to-real transferability of existing methods, awareness of victims' conditions, coordination and interoperability in heterogeneous multi-robot systems, and active perception. The different topics in the survey are put in the context of the different challenges and constraints that various types of robots (ground, aerial, surface, or underwater) encounter in different SAR environments (maritime, urban, wilderness, or other post-disaster scenarios). The objective of this survey is to serve as an entry point to the various aspects of multi-robot SAR systems to researchers in both the machine learning and control fields by giving a global overview of the main approaches being taken in the SAR robotics area.