Information-Criterion-Based Agent Selection for Cooperative Localization in Static Networks

Wielandner, Lukas; Leitinger, Erik; Witrisal, Klaus

doi:10.1109/iccworkshops49005.2020.9145208

“…When dealing with large networks, full cooperation is sometimes not wanted, due to resource limitations with regard to energy consumption, measurement time, and computational power. In these cases, selecting highly informative cooperating partners can be essential since at some point increasing the set of cooperating partners does not increase the positioning performance any more [11], [37], [38]. For range-based CL, there exists a variety of different approaches like convex optimization [20] or a fully Bayesian treatment of the problem as in [8], [39]- [43].…”

Section: A State Of the Art And Related Workmentioning

confidence: 99%

RSS-Based Cooperative Localization and Orientation Estimation Exploiting Antenna Directivity

Wielandner

¹

,

Leitinger

²

,

Witrisal

³

2021

Self Cite

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In this paper, we propose a factor-graph-based cooperative positioning algorithm that uses RSS radio measurements and accounts for the directivity of the antennas. This is achieved by modeling the directivity with a parametric antenna pattern and jointly estimating position and orientation of the agents. We propose two different approaches whereas the first one uses a continuous representation of the orientation state and the second one a discrete representation. We validate our proposed methods with simulations and measurements in a static sensor network with more than 900 agents in an indoor environment and show that the positioning accuracy can be improved significantly by considering the influence of orientations.

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“…TD methods use a generalized policy iteration (GPI) mechanism to alternatively estimate the optimal policy in (1) and the optimal Q-value in (3). Choose a greedy action a k ∈ A corresponds to the maximum Q-value in Q(s k , :); (exploitation) end UAV moves to the new state, collects the reward r k+1 and updates the Q-table according to (12). end…”

Section: State Estimator: Mapping With Ogmentioning

confidence: 99%

“…In [5], an information-seeking algorithm is developed for extraterrestrial exploration and return-to-base application, whereas in [8,9] a similar problem is solved using RL for source localization. Algorithms for UAVs formation, navigation and self-localization have been proposed in [10][11][12][13][14], and RL for enhancing communications has been studied in [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Learning for THZ Radar Mapping and UAV Control

Guerra

¹

,

Guidi

²

,

Dardari

³

et al. 2021

2021 IEEE International Conference on Autonomous Systems (ICAS)

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In this paper we consider a joint detection, mapping and navigation problem by an unmanned aerial vehicle (UAV) with real-time learning capabilities. We formulate this problem as a Markov decision process (MDP), where the UAV is equipped with a THz radar capable to electronically scan the environment with high accuracy and to infer its probabilistic occupancy map. The navigation task amounts to maximizing the desired mapping accuracy and coverage and to decide whether targets (e.g., people carrying radio devices) are present or not. With the numerical results, we analyze the robustness of the considered Q-learning algorithm, and we discuss practical applications.

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“…When dealing with large networks, full cooperation is sometimes not wanted, due to resource limitations with regard to energy consumption, measurement time, and computational power. In these cases, selecting highly informative cooperating partners can be essential since at some point increasing the set of cooperating partners does not increase the positioning performance any more [11], [37], [38]. For range-based CL, there exists a variety of different approaches like convex optimization [20] or a fully Bayesian treatment of the problem as in [8], [39]- [43].…”

Section: A State Of the Art And Related Workmentioning

confidence: 99%

RSS-based Cooperative Localization and Orientation Estimation Exploiting Directive Antenna Patterns

Wielandner¹,

Leitinger²,

Witrisal³

2021

Preprint

Self Cite

0

View full text Add to dashboard Cite

In this paper, we propose a factor-graph-based cooperative positioning algorithm that uses RSS radio measurements and accounts for the directivity of the antennas. This is achieved by modeling the directivity with a parametric antenna pattern and jointly estimating position and orientation of the agents. We propose two different approaches whereas the first one uses a continuous representation of the orientation state and the second one a discrete representation. We validate our proposed methods with simulations and measurements in a static sensor network with more than 900 agents in an indoor environment and show that the positioning accuracy can be improved significantly by considering the influence of orientations.

show abstract

Information-Criterion-Based Agent Selection for Cooperative Localization in Static Networks

Cited by 4 publications

References 17 publications

RSS-Based Cooperative Localization and Orientation Estimation Exploiting Antenna Directivity

RSS-Based Cooperative Localization and Orientation Estimation Exploiting Antenna Directivity

Real-Time Learning for THZ Radar Mapping and UAV Control

RSS-based Cooperative Localization and Orientation Estimation Exploiting Directive Antenna Patterns

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