Multi-robot exploration controlled by a market economy

By Robert Zlot, Anthony Stentz, M. Dias, S. Thayer. Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), 2002

647 citations recorded by the source corpus.

Presents an approach to efficient multirobot 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 being able to withstand communication interruptions and failures. Results showing the capabilities of our system on a team of exploring autonomous robots are given.

Subfields: Computer Networks and Communications, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/66810d603501f1cd030e370e29dc5c20467bb126

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In Computer Networks and Communications

In Management Science and Operations Research

Citations in the corpus

Distributed Intelligence: Overview of the Field and Its Application in Multi-Robot Systems (2008, background): “A significant amount of recent work addresses more powerful market-based approaches for task allocation [39], [58], [96], [117], [61], [11], [91], [127], [42], [52], [64], [32], [50], [85].”
Multiple‐Robot Simultaneous Localization and Mapping: A Review (2016, background): “Multiple-robot exploration (Rekleitis et al., 2001; Zlot et al., 2002; Burgard and Schneider, 2002; Sheng et al., 2006; Burgard et al., 2005; Wurm et al., 2008) is also another interesting topic which is tightly coupled with multiple-robot SLAM.”
Anytime Dynamic A*: An Anytime, Replanning Algorithm (2005, methodology): “D* has been shown to be up to two orders of magnitude more efficient than planning from scratch with A*, and it has been used extensively by fielded robotic systems (Stentz & Hebert 1995; Hebert, McLachlan, & Chang 1999; Matthies et al. 2000; Thayer et al. 2000; Zlot et al. 2002).”
Market-Based Multirobot Coordination: A Survey and Analysis (2006, background): “[8, 18, 45, 44, 23, 39, 38]), market-based approaches have yet to be proven in a wide variety of domains.”
Multi-robot Task Allocation: A Review of the State-of-the-Art (2015, background): “environments by allowing team members to adapt cost estimates over time, and reallocate tasks when appropriate [44].”
Coordinated multi-robot exploration using a segmentation of the environment (2008, background): “In many approaches, the robots are assigned directly to frontier targets based on a cost function that takes into account the expected path costs or travel time as well as a utility function that covers aspects such as the expected gain in information [3], [9], [21], [24], [28].”
A Formal Analysis and Taxonomy of Task Allocation in Multi-Robot Systems (2004, methodology): “This idea is demonstrated by the multi-robot exploration system described by Zlot, Stentz, Dias & Thayer (2002) .”
Distributed Multirobot Exploration and Mapping (2005, methodology): “If the robots know their relative locations and share a map of the area they explored so far, then effective coordination can be achieved by guiding the robots into different, non-overlapping areas of the environment [1], [29], [37], [2].”
Coordinated Multi-Robot Exploration Under Communication Constraints Using Decentralized Markov Decision Processes (2012, background): “Global coordination can also be decentralized as in (Zlot et al. 2002) where robots bid on targets to negotiate their assignments.”
Coordinated multi-robot exploration (2005, background): “However, in the case of multiple robots this TSP-approach can be disadvantageous.”
A Survey and Analysis of Multi-Robot Coordination (2013, neutral): “Some works considering the use of homogeneous robot teams include [28] [29] [30] [31] [24].”