Cooperative Mapping and Target Search Over an Unknown Occupancy Graph Using Mutual Information

Wolek, Artur; Cheng, Sheng; Goswami, Debdipta; Paley, Derek A.

doi:10.1109/lra.2020.2966394

Cited by 16 publications

(7 citation statements)

References 28 publications

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“…There are mainly two kinds of UAV search tasks, one of which is to search one or more specific targets in known areas with minimum cost, 17 and the other is to control UAVs for maximum coverage search efficiently in unknown areas. 29 It is noted that autonomous target search has not been taken into account in most UAV IBVS studies, which generally require manual operation for visual target observation.…”

Section: Introductionmentioning

confidence: 99%

Visual servoing of quadrotor UAVs for slant targets with autonomous object search

Shi

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part I:

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In this paper, an enhanced visual servoing method is designed for a quadrotor unmanned aerial vehicle (UAV) based on virtual plane image moments, under underactuation and tight coupling constraints of UAV kinematics. Moreover, in order to make the UAV search visual targets autonomously in target vicinity during flight, a flexible flight system is developed with stages of take-off, target searching, and image-based visual servoing (IBVS). With dual-camera sensor configuration, the UAV system searches targets from given directions while making localization. A virtual image plane is constructed and image moments are adopted to decouple UAV lateral movement. For a non-horizonal target, homography is utilized to construct the target plane and transform it into a horizonal plane. Backstepping techniques are used to derive the nonlinear controller to realize the IBVS strategy. Stability analysis proves global asymptotic performance of the closed-loop system. Experimental verification shows feasibility of the overall flight system and effectiveness of the visual servoing controller.

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Section: Introductionmentioning

confidence: 99%

Visual servoing of quadrotor UAVs for slant targets with autonomous object search

Shi

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part I:

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“…With this characteristic, exploratory actions are associated with those that have high levels of uncertainty, while exploitative ones are associated with low levels of uncertainty. In MAS operating in unknown environments, these uncertainties are usually presented in the form of a map that updates itself as the task progresses (Wolek et al, 2020;Crosscombe and Lawry, 2021;Liu et al, 2021). Using such maps allows an agent to move towards regions of different levels of uncertainty based on its intentions to carry out either exploration or exploitation.…”

Section: Introductionmentioning

confidence: 99%

Balancing Collective Exploration and Exploitation in Multi-Agent and Multi-Robot Systems: A Review

2022

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Multi-agent systems and multi-robot systems have been recognized as unique solutions to complex dynamic tasks distributed in space. Their effectiveness in accomplishing these tasks rests upon the design of cooperative control strategies, which is acknowledged to be challenging and nontrivial. In particular, the effectiveness of these strategies has been shown to be related to the so-called exploration–exploitation dilemma: i.e., the existence of a distinct balance between exploitative actions and exploratory ones while the system is operating. Recent results point to the need for a dynamic exploration–exploitation balance to unlock high levels of flexibility, adaptivity, and swarm intelligence. This important point is especially apparent when dealing with fast-changing environments. Problems involving dynamic environments have been dealt with by different scientific communities using theory, simulations, as well as large-scale experiments. Such results spread across a range of disciplines can hinder one’s ability to understand and manage the intricacies of the exploration–exploitation challenge. In this review, we summarize and categorize the methods used to control the level of exploration and exploitation carried out by an multi-agent systems. Lastly, we discuss the critical need for suitable metrics and benchmark problems to quantitatively assess and compare the levels of exploration and exploitation, as well as the overall performance of a system with a given cooperative control algorithm.

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“…Moreover, it can easily get trapped into local optima as well. To further investigate the search efficiency in more complex environments, Wolek et al [12] propose a weighted Voronoi-based region decomposition strategy. Cooperative mapping and target-track-before-detect algorithm are designed to guide agents to search for a moving target in a congested urban environment.…”

Section: Introductionmentioning

confidence: 99%

Multiagent coverage search based on Voronoi and sparse heteroscedastic Gaussian process

Meng

Cai

et al. 2022

Asian Journal of Control

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This work is concerned with multiagent cooperative and autonomous coverage search in an unknown environment. A novel Voronoi and sparse heteroscedastic Gaussian process (SHGP)-based search method is proposed to improve the target search efficiency. By means of heteroscedastic Gaussian process (HGP), each agent can estimate the probability of target existence in given locations online according to the local probability map. Then, these local probability maps are fused together to obtain a posterior probability distribution for target prediction. Based on that, the agents' search paths within Voronoi cells will be adjusted adaptively online to make sure all the agents can search for targets more efficiently. A challenging issue then falls in the computational complexity of the HGP. To solve this problem, we propose an adaptive ranked-set sampling algorithm based on the weighted sampling process and K-means clustering algorithm. Theoretical analysis on the discrepancy of the kernel matrix between the original probability points and the sampling points is also given. Simulation results demonstrate that our proposed coverage search method can improve the performance of the area search compared with the existing Voronoi-based one.

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Cooperative Mapping and Target Search Over an Unknown Occupancy Graph Using Mutual Information

Cited by 16 publications

References 28 publications

Visual servoing of quadrotor UAVs for slant targets with autonomous object search

Visual servoing of quadrotor UAVs for slant targets with autonomous object search

Balancing Collective Exploration and Exploitation in Multi-Agent and Multi-Robot Systems: A Review

Multiagent coverage search based on Voronoi and sparse heteroscedastic Gaussian process

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