A coalition formation algorithm for Multi-Robot Task Allocation in large-scale natural disasters

Abstract

Abstract-In large-scale natural disasters, humans are likely to fail when they attempt to reach high-risk sites or act in search and rescue operations. Robots, however, outdo their counterparts in surviving the hazards and handling the search and rescue missions due to their multiple and diverse sensing and actuation capabilities. The dynamic formation of optimal coalition of these heterogeneous robots for cost efficiency is very challenging and research in the area is gaining more and more attention. In this paper, we propose a novel heuristic. Since the population of robots in large-scale disaster settings is very large, we rely on Quantum Multi-Objective Particle Swarm Optimization (QMOPSO). The problem is modeled as a multi-objective optimization problem. Simulations with different test cases and metrics, and comparison with other algorithms such as NSGA-II and SPEA-II are carried out. The experimental results show that the proposed algorithm outperforms the existing algorithms not only in terms of convergence but also in terms of diversity and processing time.

Toward a robot swarm protecting a group of migrants

“…The management of multi-robots could be applied in harsh environments, such as mountains and valleys, which contain many different kinds of obstacles [5][6][7][8]. On these difficult fields, some properties of swarms allow them to adapt their behavior to face situations like damage of one of their robots.…”

“…In addition, external factors must be taken into account to provide a safety zone around the group of migrants. With respect to this challenge, some studies have been conducted regarding a mobile group of moving rovers interacting with external factors that have an impact on the group's decision [5][6][7][8]. The suggested system should track the migrants, compute some optimal way-points around the migrants and manage the robot's faults.…”

“…We chose to detect four situations, one normal and three abnormal states: a normal move of a rover on stones, a fall of one rover, a collision with an obstacle, and a skid on sand. Methods of human-swarm interaction mostly rely on orders given by operators via different interfaces, like computers and smart watches [5][6][7][8]. The level of automation is reduced with such interface.…”

Blockchain-based framework for ontology-oriented robots’ coalition formation in cyberphysical systems

“…To date, many solutions have been proposed in the field of collective decentralized robot control systems. In works [2,5,6,8,9] models and algorithms for solving problems of optimal distribution of goals between robots of the group are presented, as well as algorithms for collective control of robots in conditions of active counteraction from the environment. Original methods for solving the problem of controlling large groups of robots are proposed.…”

“…The robots' coalition formation with the distribution of tasks among all coalition members is an NP-complete task. To date, many solutions have been proposed that provide an approximate solution to the coalition forming task [2,[4][5][6][7]. Another important task in the robots coalition formation is the organization of an information interaction environment between them, which allows information exchanging about the current situation and the distribution of tasks among the participants in the coalition.…”