Detail of the student project

List
Topic:Decision-Making on Collaborative Informative Path Planning
Department: Multirobotické systémy
Supervisor:Giovanni Reina
Announce as:Diplomová práce, Bakalářská práce, Semestrální projekt
Description:UAVs offer a relatively risk-free and low-cost way to quickly and systematically observe phenomena and targets at high spatio-temporal resolution. One important capability that a multi-UAV system needs to have to cooperate effectively is the ability to make collective decisions. In general, to make a collective decision, robots share their information and aggregate this information using a consensus protocol. Consensus achievement is a crucial capability for multi-UAVs, for example, for path selection, spatial aggregation, or collective sensing. However, the presence of malfunctioning and malicious robots can make it impossible to achieve consensus. To deal with this problem and be deployed in the real world, it is necessary that UAVs recognize the presence of these faults to make decisions. In this work, we will investigate how a multi-UAV system can achieve consensus by exploiting blockchain-based smart technology to improve collaborative Informative Path Planning. The goal of this project is to develop a blockchain-based multi-UAV system that is capable of achieving consensus in the presence of malicious and faulty UAVs. The proposed system will use smart contracts to store and update the UAVs' information in a secure and distributed ledger. This information will be used to identify malicious and faulty UAVs and ensure that the consensus is achieved. The system will also use blockchain to ensure secure communication between UAVs and provide transparent, secure, and verifiable data exchange. To evaluate the performance of the proposed system, we will conduct simulations using a multi-UAV system with different numbers of UAVs and different levels of malicious and faulty UAVs.
Bibliography:- Zhao, Z.; Zhu, B.; Zhou, Y.; Yao, P.; Yu, J. Cooperative Path Planning of Multiple Unmanned Surface Vehicles for Search and Coverage Task. Drones 2023, 7, 21. https://doi.org/10.3390/drones7010021
- Denniston, Christopher E., et al. "Fast and Scalable Signal Inference for Active Robotic Source Seeking." (2023).
- Strobel, Volker, Eduardo Castelló Ferrer, and Marco Dorigo. "Blockchain technology secures robot swarms: A comparison of consensus protocols and their resilience to Byzantine robots." Frontiers in Robotics and AI 7 (2020): 54.
Responsible person: Petr Pošík