Active target localization for bearing based robotic telemetry

Tokekar, P.; Hook, Joshua Vander; Isler, V.

doi:10.1109/iros.2011.6048778

Cited by 11 publications

(12 citation statements)

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“…Incorporating measurement time is relevant in a variety of real-world problem settings. For example, we previously used sensors to sample radio signal strength over 1 to 2 min to discern the bearing toward the target [2], [10], [11]. Another possible measurement cost is local maneuvers during a measurement.…”

Section: Related Workmentioning

confidence: 99%

Algorithms for Cooperative Active Localization of Static Targets With Mobile Bearing Sensors Under Communication Constraints

2015

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We study the problem of actively locating a static target using mobile robots equipped with bearing sensors. The goal is to reduce the uncertainty in the target's location to a value below a given threshold in minimum time. Our cost formulation explicitly models time spent in traveling, as well as taking measurements. In addition, we consider distance-based communication constraints between the robots. We provide the following theoretical results. First, we study the properties of an optimal offline strategy for one or more robots with access to the target's true location. We derive the optimal offline algorithm and bound its cost when considering a single robot or an even number of robots. In other cases, we provide a close approximation. Second, we provide a general method of converting the offline algorithm into an online adaptive algorithm (that does not have access to the target's true location), while preserving near optimality. Using these two results, we present an online strategy proven to locate the target up to a desired uncertainty level at near-optimal cost. In addition to theoretical analysis, we validate the algorithm in simulations and multiple field experiments performed using autonomous surface vehicles carrying radio antennas to localize radio tags.Index Terms-Localization, marine robotics, networked robots, path planning for multiple mobile robot systems.

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Section: Related Workmentioning

confidence: 99%

Algorithms for Cooperative Active Localization of Static Targets With Mobile Bearing Sensors Under Communication Constraints

2015

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“…In Tokekar et al. () and Tokekar, Vander Hook, and Isler (), we investigated three algorithms to find measurement locations, each based on a search over the discretized space around the robot. Discretization and search over state space was computationally demanding, and the results were limited to a fixed‐sized displacement between measurements because of the discretization size.…”

Section: Related Workmentioning

confidence: 99%

“…To find a bearing with maximum signal strength that does not lie directly on a sampled orientation, we fit a polynomial to the samples and solve for the bearing of maximum signal strength as shown in Tokekar et al. (). We have established from field trials that the process of taking a bearing measurement requires approximately 1–2 min.…”

Section: Field Experimentsmentioning

confidence: 99%

Cautious Greedy Strategy for Bearing‐only Active Localization: Analysis and Field Experiments

Hook

Tokekar

Isler

2014

Journal of Field Robotics

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We study the problem of optimally choosing bearing measurement locations for localizing a stationary target in minimum time. The targets are transmitting radio tags, and bearing measurements are acquired from radio signal strength by a robot carrying a direction‐sensitive radio antenna. Actively localizing radio tags has many applications in surveillance, search and rescue, and environmental monitoring. Our work is motivated by the task of monitoring radio‐tagged invasive fish using autonomous vehicles. An active localization algorithm is provided in order to locate a target up to the desired uncertainty. The time required to locate the target includes time spent traveling as well as taking measurements. Since bearing measurements inferred from radio signals have an inherent ambiguity associated with them, the proposed algorithm chooses measurements to minimize the effect of ambiguous measurements on the target estimate. We present a closed‐form bound on the time required to locate a target using the presented active localization strategy. We also present the first known lower bound on the time required by any active localization algorithm (including the unknown optimal). Finally, we bound the ratio of the upper and lower bounds, showing that the expected cost of our algorithm is within a constant factor of the expected cost of the optimal solution. Robust initialization strategies that are motivated by practical sensing limitations are also provided. Our algorithm is shown to reliably locate radio tags to a desired uncertainty in simulations and multiple field experiments.

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“…For this reason, active sensing that finds the optimal path or trajectory for information gain maximisation can yield significant benefits to improving the perceptual results in target localisation (Bajcsy et al, 2018). Through numerically maximising the determinant of FIM over a finite horizon, optimal observer trajectory for bearing measurements gathering a https://orcid.org/0000-0001-6432-5187 b https://orcid.org/0000-0001-9938-0370 c https://orcid.org/0000- 0002-3966-7633 to localize a single target was proposed in Tokekar et al (2011). The rationale of leveraging FIM lies in that it prescribes a lower bound of target localisation error covariance of any efficient estimation algorithm (Taylor, 1979).…”

Section: Introductionmentioning

confidence: 99%

Optimal Active Target Localisation Strategy with Range-only Measurements

Shin

Tsourdos

2019

Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics

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This paper investigates the problem of one-step ahead optimal active sensing strategy to minimise estimation errors with range-only measurements for non-manoeuvring target. The determinant of Fisher Information Matrix (FIM) is utilized as the objective function in the proposed optimisation problem since it quantifies the volume of uncertainty ellipsoid of any efficient estimator. In consideration of physical velocity and turning rate constraints, the optimal heading angle command that maximises the cost function is derived analytically. Simulations are conducted to validate the analytical findings.

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Active target localization for bearing based robotic telemetry

Cited by 11 publications

References 0 publications

Algorithms for Cooperative Active Localization of Static Targets With Mobile Bearing Sensors Under Communication Constraints

Algorithms for Cooperative Active Localization of Static Targets With Mobile Bearing Sensors Under Communication Constraints

Cautious Greedy Strategy for Bearing‐only Active Localization: Analysis and Field Experiments

Optimal Active Target Localisation Strategy with Range-only Measurements

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