Cited By
View all- Brent SYuan CStegagno P(2022)Swarm Localization Through Cooperative Landmark IdentificationDistributed Autonomous Robotic Systems10.1007/978-3-030-92790-5_33(429-441)Online publication date: 3-Jan-2022
Cooperative place recognition in robotic swarms
Pages 785 - 792
Abstract
In this paper we propose a study on landmark identification as a step towards a localization setup for real-world robotic swarms setup. In real world, landmark identification is often tackled as a place recognition problem through the use of computationally intensive Convolutional Neural Networks. However, the components of a robotic swarm usually have limited computational and sensing capabilities that allows only for the application of relatively shallow networks that results in large percentage of recognition errors. In a previous attempt of solving a similar setup - cooperative object recognition - the authors of [1] have demonstrated how the use of communication among a swarm and a naive Bayes classifier was able to substantially improve the correct recognition rate. An assumption of that paper not compatible with a swarm localization setup was that all swarm components would be looking at the same object. In this paper, we propose the use of a weighting factor to relapse this assumption. Through the use of simulation data, we show that our approach provides high recognition rates even in situations in which the robots would look at different objects.
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- Cooperative place recognition in robotic swarms
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Published In
March 2021
2075 pages
ISBN:9781450381048
DOI:10.1145/3412841
- Conference Chairs:
- Chih-Cheng Hung,
- Jiman Hong,
- Program Chairs:
- Alessio Bechini,
- Eunjee Song
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Published: 22 April 2021
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Cited By
View all- Brent SYuan CStegagno P(2022)Swarm Localization Through Cooperative Landmark IdentificationDistributed Autonomous Robotic Systems10.1007/978-3-030-92790-5_33(429-441)Online publication date: 3-Jan-2022
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