Experimental validation of cooperative environmental boundary tracking with on-board sensors

Joshi, Abhijeet; Ashley, Trevor T.; Huang, Yuan; Bertozzi, Andrea L.

doi:10.1109/acc.2009.5159837

Cited by 60 publications

(40 citation statements)

References 16 publications

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“…Various methods for using this nonlocal information while preserving the speed of the algorithm are presented in the next section. Also, robots used in experiments [33,37] make smooth changes of direction, but this restriction is not required in the image processing case. Lastly, robots have a fixed position at any point in time and cannot make instantaneous jumps.…”

Section: Local Sampling To Track the Boundarymentioning

confidence: 99%

“…In particular, the CUSUM algorithm has been used to improve tracking performance in the environmental tracking problem [40,37]. This section reviews relevant information from change-point detection and its application to the boundary tracking problem.…”

Section: Change-point Decisionsmentioning

confidence: 99%

“…It was proposed [36] that the use of a change-point detection algorithm such as Page's cumulative sum (CUSUM) procedure [50] would allow objects to be tracked in noise. Testbed implementations of the boundary tracking algorithm suggest that robots can indeed track boundaries efficiently in the presence of a moderate amount of sensor noise [37].…”

Section: Introductionmentioning

confidence: 99%

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Efficient Boundary Tracking Through Sampling

Chen

Wittman

Tartakovsky

et al. 2011

Applied Mathematics Research eXpress

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The proposed algorithm for image segmentation is inspired by an algorithm for autonomous environmental boundary tracking. The algorithm relies on a tracker that traverses a boundary between regions in a sinusoidal-like path. Boundary tracking is done by efficiently sampling points, resulting in a significant savings in computation time. Page's cumulative sum (CUSUM) procedure and other methods are adapted to handle a high level of noise. Applications to large data sets such as hyperspectral are of particular interest. Irregularly shaped boundaries such as fractals are also treated at very fine detail.

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Section: Local Sampling To Track the Boundarymentioning

confidence: 99%

Section: Change-point Decisionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Efficient Boundary Tracking Through Sampling

Chen

Wittman

Tartakovsky

et al. 2011

Applied Mathematics Research eXpress

Self Cite

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“…Data gathered from all vehicles is used to estimate boundary. The tracking algorithm was validated in static environment using testbed in [33]. The same algorithm was used in [34] to estimate phenomena cloud boundary with single mobile node.…”

Section: Related Workmentioning

confidence: 99%

Comparison of MANET self-organization methods for boundary detection/tracking of heavy gas cloud

Krzyszton

2016

Annals of Computer Science and Information Systems

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Abstract-Mobile wireless ad hoc network (MANET) becomes increasingly popular in responding to emergency situation. In this paper a possibility to support rescue team in monitoring heavy gas cloud with MANET comprised of mobile sensing devices is investigated. In the view of the current state of research, two methods for controlling mobile sensing devices during MANET self-organization are presented. The first one is based on a greedy approach whereas the second on a repulsion from the estimated centroid of a cloud and other nodes. Various variants of both methods are considered and their efficiency in terms of detection quality and energy saving is evaluated with MobASim simulation software. The results are discussed and one variant is chosen as the basis for the future research.

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“…The distance of the robot from a discovered boundary becomes minimized as it moves back and forth across a boundary in [1]. Multiple robots are used to collect and analyze information to follow the boundary closely in a convoy.…”

Section: Chapter 2 Backgroundmentioning

confidence: 99%

Multiple Robot Boundary Tracking with Phase and Workload Balancing

Obispo¹

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Multiple Robot Boundary Tracking with Phase and Workload Balancing Michael J. Boardman This thesis discusses the use of a cooperative multiple robot system as applied to distributed tracking and sampling of a boundary edge. Within this system the boundary edge is partitioned into subsegments, each allocated to a particular robot such that workload is balanced across the robots. Also, to minimize the time between sampling local areas of the boundary edge, it is desirable to minimize the difference between each robot's progression (i.e. phase) along its allocated sub segment of the edge. The paper introduces a new distributed controller that handles both workload and phase balancing. Simulation results are used to illustrate the effectiveness of the controller in an Autonomous Underwater Vehicle (AUV) under ice edge sampling application. Successful results from experimentation with three iRobot R ⃝ Creates are also presented.iv

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Experimental validation of cooperative environmental boundary tracking with on-board sensors

Cited by 60 publications

References 16 publications

Efficient Boundary Tracking Through Sampling

Efficient Boundary Tracking Through Sampling

Comparison of MANET self-organization methods for boundary detection/tracking of heavy gas cloud

Multiple Robot Boundary Tracking with Phase and Workload Balancing

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