&lt;title&gt;Multiple robot system for decentralized SLAM investigations&lt;/title&gt;

Deaves, Rob H.; Nicholson, David; Gough, David W.; Binns, Lewis A.; Vangasse, Paul; Greenway, Phil

doi:10.1117/12.403747

Cited by 6 publications

(3 citation statements)

References 10 publications

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“…This follows logically from the update stage of the information filter which is associative and the fact that the process noise acts only on the vehicle. Further research into information space SLAM can be found in Deaves et al (2000), Nettleton et al (2000b) and Thrun et al (2002) with promising results. Using this approach and the decentralized framework presented earlier in this paper, a multi-vehicle SLAM algorithm capable of robust communications can be generated.…”

Section: Ddfslammentioning

confidence: 99%

The ANSER Project: Data Fusion Across Multiple Uninhabited Air Vehicles

Sukkarieh

Nettleton

Kim

et al. 2003

The International Journal of Robotics Research

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The objective of the autonomous navigation and sensing experiment research (ANSER) project is to demonstrate decentralized data fusion (DDF) and simultaneous localization and map building (SLAM) across multiple uninhabited air vehicles (UAVs). To achieve this objective, the project specifies the development of four UAVs, where each UAV houses up to two terrain sensors and an INS/GPS navigation system. The terrain sensors include a scanning radar, laser/vision and standard vision system. The DDF concept has to be shown to be effective both on a single UAV and on multiple UAVs. The proof of the concept will lie in the ability of the DDF structure to conduct multi-target tracking problems as well as SLAM. To obtain this goal, a number of subgoals are required, most of which have never been attempted before on a research level. The objective of this paper is to present these goals as an overview of the ANSER project along with some simulated and real-time results.

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Section: Ddfslammentioning

confidence: 99%

The ANSER Project: Data Fusion Across Multiple Uninhabited Air Vehicles

Sukkarieh

Nettleton

Kim

et al. 2003

The International Journal of Robotics Research

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“…The recent researches on such areas of MRS are motion planning, task planning, coordinate control, etc. In the field of multi-robot system, task allocation is an issue which is received much attention, and widely used in applications research, such as the exploring environments [1][2][3] , SLAM [4] , robot soccer [5] , searching and rescuing [6] , etc. For cooperative task allocation, market-based multi-robot task assignment approaches have been received significant attention and are growing in popularity within the robotics research community.…”

Section: Introductionmentioning

confidence: 99%

Self-Organizing Task Allocation of Multi-robot

Zhang

Liu³

et al. 2009

2009 Fourth International Conference on Internet Computing for Science and Engineering

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This existing multi-robot task allocation mechanisms treat tasks as simple, indivisible entities. Also in many applications, the dynamicity and complexity of the environment are not considered. In order to allocate the robots adaptively and flexibility according to the complex task and environment, this paper presents a multi-robot coordination approaches based on virtual pheromone which is inspired by the ant colony foraging behavior in the background of exploring unknown environments by multirobot system. Numerical and experiment results show that this approach is helpful and reliable, and it is proved that the robots collaboration degree was obviously improved. In addition, the exploration efficiency was greatly improved.

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“…[6][7][8][9][10][11][12] Recently, research has begun on information space implementations of the problem, 13 leading to a decentralised SLAM architecture. Closed form solutions to the continuous time problem have been presented.…”

Section: Introductionmentioning

confidence: 99%

<title>Multiple-platform localization and map building</title>

et al. 2000

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This paper presents current work on decentralised data fusion (DDF) applied to multiple unmanned aerial vehicles. The benefits of decentralising algorithms, particularly in this field, are enormous. At a mission level, multiple aircraft may fly together sharing information with one another in order to produce more accurate and coherent estimates, and hence increase the their chances of success. At the single platform level, algorithms may be decentralised throughout the airframe reducing the probability of catastrophic failure by eliminating the dependency on a particular central processing facility.To this end, a complex simulator has been developed to test and evaluate decentralised picture compilation, platform localisation and simultaneous localisation and map building (SLAM) algorithms which are to be implemented on multiple airborne vehicles. This simulator is both comprehensive and modular, enabling multiple platforms carrying multiple distributed sensors to be modelled and interchanged easily. The map building and navigation algorithms interface with both the simulator and the real airframe in exactly the same way in order to evaluate the actual flight code as comprehensively as possible. Logged flight data can also be played back through the simulator to the navigation routines instead of simulated sensors. This paper presents the structure of both the simulator and the algorithms that have been developed. An example of decentralised map building is included, and future work in decentralised navigation and SLAM systems is discussed.

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<title>Multiple robot system for decentralized SLAM investigations</title>

Cited by 6 publications

References 10 publications

The ANSER Project: Data Fusion Across Multiple Uninhabited Air Vehicles

The ANSER Project: Data Fusion Across Multiple Uninhabited Air Vehicles

Self-Organizing Task Allocation of Multi-robot

<title>Multiple-platform localization and map building</title>

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