Market-Driven Multi-Robot Exploration

Abstract

Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. AbstractFor many real-world applications, autonomous robots must execute complex tasks in unknown or partially known unstructured environments. This work presents a novel approach to efficient multi-robot mapping and exploration which exploits a market architecture in order to maximize information gain while minimizing incurred costs. This system is reliable and robust in that it can accommodate dynamic introduction and loss of team members in addition to communication interruptions and failures. Results showing the capabilities of our system on a team of exploring autonomous robots are also given.I

Hoplites: A Market-Based Framework for Planned Tight Coordination in Multirobot Teams

“…Market frameworks have all the benefits of distributed approaches including robustness, speed, and flexibility [13], [14], [15]. Resources permitting, they can also be more centralized to produce better solutions [16]: a robot can plan a more cost-effective task distribution for part of the team, bid on the tasks, and use the cost savings between the two distributions to purchase team members' participation.…”

Potential Field Based Integrated Exploration for Multi-Robot Teams

“…A group of exploration methods employ path planning techniques in order to direct the robots to the frontier cells (Simmons et al, 2000;Burgard et al, 2005;Zlot et al, 2002). They differ in the coordination strategies used to assign a frontier to each robot: the robots can go to the nearest frontier (Yamauchi, 1997) or they can follow a cost-utility model to make their assignments.…”

“…consider in the utility function the proximity of frontiers assigned to other robots. (Zlot et al, 2002) suggest using a market economy where the robots negotiate their assignments.…”

Comparative Study of Market-Based and Threshold-Based Task Allocation

“…This price-driven redistribution simultaneously results in better team solutions. Market-based task allocation has also been proven on a number of domains including as exploration [4] and object manipulation [5].…”

“…Respectively, handling could involve robots fixing broken machines and making deliveries. Event-handling can also be mapped onto domains that are currently solved by market-based approaches (e.g., exploration [4]) and threshold-based approaches (e.g., foraging [2]). …”