The majority of today's navigation techniques for intelligent transportation systems use Global Positioning Systems (GPS) that can provide position information with bounded errors. However, because of the low accu...
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The majority of today's navigation techniques for intelligent transportation systems use Global Positioning Systems (GPS) that can provide position information with bounded errors. However, because of the low accuracy and multi-path problem, it is challenging to determine a vehicle's position at lane level. With Markov-based approach based on sharing information among a group of vehicles that are traveling close to each other, the lane positions of vehicles can be found. The algorithm shows its effectiveness in both simulations and experiments with real data
This paper addresses the challenging problem of finding collision- free trajectories for many robots moving to individual goals within a common environment. Most popular algorithms for multi-robot planning manage the ...
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ISBN:
(纸本)8587978128
This paper addresses the challenging problem of finding collision- free trajectories for many robots moving to individual goals within a common environment. Most popular algorithms for multi-robot planning manage the complexity of the problem by planning trajectories for robots sequentially, such decoupled methods may fail to and a solution even if one exists. In contrast, this paper describes a multi-phase approach to the planning problem that guarantees a solution by creating and maintaining obstacle-free paths through the environment as required for each robot to reach its goal. Using a topological graph and spanning tree representation of a tunnel or corridor environment, the multi-phase planner is capable of planning trajectories for up to r = L¡1 robots, where the spanning tree includes L leaves. Monte Carlo simulations in a large environment with varying number of robots demonstrate that the algorithm can solve planning problems requiring complex coordination of many robots that cannot be solved with a decoupled approach, and is scalable with complexity linear in the number of robots.
This paper addresses the challenging problem of finding collision-free trajectories for many robots moving to individual goals within a common environment. Most popular algorithms for multi-robot planning manage the c...
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This paper addresses the challenging problem of finding collision-free trajectories for many robots moving to individual goals within a common environment. Most popular algorithms for multi-robot planning manage the complexity of the problem by planning trajectories for robots sequentially; such decoupled methods may fail to find a solution even if one exists. In contrast, this paper describes a multi-phase approach to the planning problem that guarantees a solution by creating and maintaining obstacle-free paths through the environment as required for each robot to reach its goal. Using a topological graph and spanning tree representation of a tunnel or corridor environment, the multi-phase planner is capable of planning trajectories for up to r = L – 1 robots, where the spanning tree includes L leaves. Monte Carlo simulations in a large environment with varying number of robots demonstrate that the algorithm can solve planning problems requiring complex coordination of many robots that cannot be solved with a decoupled approach, and is scalable with complexity linear in the number of robots.
This paper presents the design of a distributed sensing system that uses an Extended Kalman Filter (EKF) to fuse measurements, so that automotive vehicle states can be estimated for use by a Semi-active Suspension con...
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This book constitutes the refereed proceedings of the 13th Conference on Towards autonomous Robotic Systems, TAROS 2012 and the 15th Robot World Congress, FIRA 2012, held as joint conference in Bristol, UK, in August ...
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ISBN:
(数字)9783642325274
ISBN:
(纸本)9783642325267
This book constitutes the refereed proceedings of the 13th Conference on Towards autonomous Robotic Systems, TAROS 2012 and the 15th Robot World Congress, FIRA 2012, held as joint conference in Bristol, UK, in August 2012. The 36 revised full papers presented together with 25 extended abstracts were carefully reviewed and selected from 89 submissions. The papers cover various topics in the field of autonomousrobotics.
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