Collaborative Multi-Robot Localization

Fox, Dieter; Burgard, Wolfram; Kruppa, Hannes; Thrun, Sebastian

doi:10.1007/978-3-642-60243-6_2

Cited by 158 publications

(180 citation statements)

References 7 publications

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“…We do not aspire to contend with state-of-the-art solutions for the general collaborative map-making problem, which has been in the focus of research in the domain of mobile robots for decades (cf. to the work by Burgard, Fox, et al [7,8], for instance). Our primary goal is to demonstrate the feasibility and practicability of using a superdistributed RFID tag infrastructure for the realization of collaborative activities, which is not considered by traditional map-making systems.…”

Section: Collaborative Sdri Mapping Prototypementioning

confidence: 86%

Prototypical Implementation of Location-Aware Services Based on Super-Distributed RFID Tags

Bohn

2006

Lecture Notes in Computer Science

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Abstract. We provide evidence of the feasibility and effectiveness of a middleware architecture for mobile devices which employs dense distributions of small computerized entities for providing fault-tolerant location-aware services. We do so by describing exemplary implementations based on radio frequency identification (RFID) as an enabling technology. Firstly, we present prototypical implementations of the hardware abstraction layer and of selected core middleware services. The latter enable a mobile device to store and retrieve data and position information in physical places in a fault-tolerant manner, and to identify places based on a location abstraction which is robust against failure of individual tags. Secondly, we investigate the feasibility of some higher-level services and applications by developing and evaluating prototypical systems for tracing and tracking, self-positioning, and collaborative map-making.

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Section: Collaborative Sdri Mapping Prototypementioning

confidence: 86%

Prototypical Implementation of Location-Aware Services Based on Super-Distributed RFID Tags

Bohn

2006

Lecture Notes in Computer Science

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“…Areas of investigation include localization [23,28,71], mapping and exploration [19,89], and strategies to manage wireless connectivity among robots [77]. With simultaneous localization and mapping (SLAM) [3,39,46,94], additional information from several robots can simplify a problem and speed the solution that would have been provided by a single robot [28]; although multi-robot SLAM can also lead to inconsistency in position estimates [47,58]. Other challenges for a multi-robot team are similar to those for one robot, complicated by the need to merge or expand single-robot solutions to incorporate other robots.…”

Section: Related Workmentioning

confidence: 99%

Designing the HRTeam Framework: Lessons Learned from a Rough-and-Ready Human/Multi-Robot Team

Sklar

Ozgelen

Muñoz

et al. 2012

Advanced Agent Technology

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Abstract. In this workshop paper, we share the design and on-going implementation of our HRTeam framework, which is constructed to support multiple robots working with a human operator in a dynamic environment. The team is comprised of one human plus a heterogeneous set of inexpensive, limited-function robots. Although each individual robot has restricted mobility and sensing capabilities, together the team members constitute a multi-function, multi-robot facility. We describe low-level system architecture details and explain how we have integrated a popular robotic control and simulation environment into our framework to support application of multi-agent techniques in a hardware-based environment. We highlight lessons learned regarding the integration of multiple varying robot platforms into our system, from both hardware and software perspectives. Our aim is to generate discussion amongst multirobot researchers concerning issues that are of particular interest and present particular difficulties to the multi-robot systems community.

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“…Even more related to this paper is work done in the field of sensor fusion. Fox has shown that when the amount of information that a robot receives is restricted, teams of robots, with different sensors, can work together to solve the robot localization problem [14]. In addition it has been shown that teams can share sensor information to estimate unobservable parts of the system in robotic soccer domains [30].…”

Section: Teamsmentioning

confidence: 99%

Handling Communication Restrictions and Team Formation in Congestion Games

Agogino

Tumer

2006

Auton Agent Multi-Agent Syst

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Abstract. There are many domains in which a multi-agent system needs to maximize a "system utility" function which rates the performance of the entire system, while subject to communication restrictions among the agents. Such communication restrictions make it difficult for agents that take actions to optimize their own "private" utilities to also help optimize the system utility. In this article we show how previously introduced utilities that promote coordination among agents can be modified to be effective in domains with communication restrictions. The modified utilities provide performance improvements of up to 75% over previously used utilities in congestion games (i.e., games where the system utility depends solely on the number of agents choosing a particular action). In addition, we show that in the presence of severe communication restrictions, team formation for the purpose of information sharing among agents leads to an additional 25% improvement in system utility. Finally, we show that agents' private utilities and team sizes can be manipulated to form the best compromise between how "aligned" an agent's utility is with the system utility and how easily an agent can learn that utility.

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Collaborative Multi-Robot Localization

Cited by 158 publications

References 7 publications

Prototypical Implementation of Location-Aware Services Based on Super-Distributed RFID Tags

Prototypical Implementation of Location-Aware Services Based on Super-Distributed RFID Tags

Designing the HRTeam Framework: Lessons Learned from a Rough-and-Ready Human/Multi-Robot Team

Handling Communication Restrictions and Team Formation in Congestion Games

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