New PDF release: Advances in Autonomous Robotics Systems: 15th Annual

By Michael Mistry, Aleš Leonardis, Mark Witkowski, Chris Melhuish

ISBN-10: 3319104004

ISBN-13: 9783319104003

ISBN-10: 3319104012

ISBN-13: 9783319104010

This booklet constitutes the refereed lawsuits of the fifteenth convention on Advances in independent Robotics, TAROS 2014, held in Birmingham, united kingdom, in September 2014. The 23 revised complete papers provided including nine prolonged abstracts have been rigorously reviewed and chosen from forty eight submissions. the general software covers a number of facets of robotics, together with navigation, making plans, sensing and conception, flying and swarm robots, ethics, humanoid robotics, human-robot interplay, and social robotics.

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Additional resources for Advances in Autonomous Robotics Systems: 15th Annual Conference, TAROS 2014, Birmingham, UK, September 1-3, 2014. Proceedings

Sample text

In such state, if the robot does not identify an obstacle in its front, the state changes again to Robot and it will start to move by formation control rules. On the other hand, if the robot identifies an obstacle in its front, the robot will rotate again to avoid it but keeping the state Rotated_robot. Once in its new orientation, the robot identifies it as a "possible corner scenario" and it will make a new step to the left to deviate from the obstacle, even if its side sensors indicate that the obstacle was overcome.

Two navigation patterns were evaluated in [14]: the triangular and the linear formations. The authors performed experiments both in simulation and with real e-pucks to validate their results. Two different types of 2D CA rules are employed in [14]: the first type is used to deviate from obstacles and the second to perform the formation control. The application of such rules is performed through a master-slave control architecture in [14], which takes in account the relative position of other robots as well and the desirable pattern.

1 Introduction Path planning is one of the most-studied tasks in autonomous robots [1]. Traditional approaches to path planning are: route maps [2], cell decomposition [3] and potential field [4]. Since they are totally discrete models, cellular automata (CA) [5], [6] have also been recently considered for path planning [7], [8], [9], [12], [13], [14], [15], [16], [17], [18]. The decentralized CA architecture permits the development of highdistributed solutions for path-planning. In this work, we investigate the model proposed by Ioannidis and collaborators [14].

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Advances in Autonomous Robotics Systems: 15th Annual Conference, TAROS 2014, Birmingham, UK, September 1-3, 2014. Proceedings by Michael Mistry, Aleš Leonardis, Mark Witkowski, Chris Melhuish


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