Cooperative Robots and Sensor Networks 2015 by Anis Koubâa, J.Ramiro Martínez-de Dios

By Anis Koubâa, J.Ramiro Martínez-de Dios

This publication compiles a number of the most recent learn in cooperation among robots and sensor networks. based in twelve chapters, this e-book addresses primary, theoretical, implementation and experimentation concerns. The chapters are geared up into 4 components particularly multi-robots structures, info fusion and localization, safety and dependability, and mobility.

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Extra info for Cooperative Robots and Sensor Networks 2015

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This problem is known as Multi-robot Task Allocation (MRTA) problem. MRTA is a complex problem especially when it comes to heterogeneous unreliable robots equipped with different capabilities that are required to perform various tasks with different requirements and constraints in an optimal way. This chapter provides a comprehensive review on challenging aspects of MRTA problem, recent approaches to tackle this problem and the future directions. A. Khamis (B) Engineering Science Department, Suez University Egypt and Vestec.

Syst. 71, 423–444 (2013) 4. : Minefield mapping using cooperative multirobot systems. J. Robot. 2012 (2012) 5. : Multi-robot teams for environmental monitoring. Innovations Defence Support Syst. 336, 183–209 (2011) 6. : Multi-domain monitoring of marine environments using a heterogeneous robot team. Intell. Robots Syst. (IROS) 1747–1753 (2012) Multi-robot Task Allocation: A Review of the State-of-the-Art 49 7. : Robotic service coordination for elderly people and caregivers with ubiquitous network robot platform.

Rk , tk ) f or 1 ≤ k ≤ m (1) For the general case, the problem is to find the optimal allocation of a set of tasks to a subset of robots, which will be responsible for accomplishing it [13]: A:T →R (2) In some MRTA approaches such as market-based approaches (Sect. 1), each robot r ∈ R can express its ability to execute a task t ∈ T, or a bundle of tasks G ⊆ T through bids br (t) or br (G). The cost of a bundle of tasks can be simply computed as the sum of costs of the individual tasks: f br (G) = br (tk ) {tk ∈ G} (3) k=1 where f is the number of tasks of the bundle G.

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