TY - GEN
T1 - Decentralized Multi-robot Velocity Estimation for UAVs Enhancing Onboard Camera-based Velocity Measurements
AU - Horyna, Jiri
AU - Kratky, Vit
AU - Ferrante, Eliseo
AU - Saska, Martin
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Within the field of multi-robot systems, developing systems that rely only on onboard sensing without the use of external infrastructure (e.g. GNSS) has many potential applications. However, relying only on visual-based modalities for localization presents challenges in terms of accuracy and reliability. We introduce a decentralized multi-robot lateral velocity estimation method for Unmanned Aerial Vehicles (UAVs) to improve onboard measurements in case GNSS infrastructure is not available. This method relies on sharing the onboard measurements of neighbors, as well as the estimation of the relative motion of a focal UAV within the swarm, based on observation of coworking robots. The proposed velocity estimation method does not rely on centralized communication to achieve high reliability and scalability within the swarm system. The performance of the state estimation approach has been verified in simulations and real-world experiments. The results have shown that a swarm of UAVs using the proposed velocity estimator can stabilize individual robots when their primary onboard localization source is not reliable enough.
AB - Within the field of multi-robot systems, developing systems that rely only on onboard sensing without the use of external infrastructure (e.g. GNSS) has many potential applications. However, relying only on visual-based modalities for localization presents challenges in terms of accuracy and reliability. We introduce a decentralized multi-robot lateral velocity estimation method for Unmanned Aerial Vehicles (UAVs) to improve onboard measurements in case GNSS infrastructure is not available. This method relies on sharing the onboard measurements of neighbors, as well as the estimation of the relative motion of a focal UAV within the swarm, based on observation of coworking robots. The proposed velocity estimation method does not rely on centralized communication to achieve high reliability and scalability within the swarm system. The performance of the state estimation approach has been verified in simulations and real-world experiments. The results have shown that a swarm of UAVs using the proposed velocity estimator can stabilize individual robots when their primary onboard localization source is not reliable enough.
UR - http://www.scopus.com/inward/record.url?scp=85146329413&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146329413&partnerID=8YFLogxK
U2 - 10.1109/IROS47612.2022.9981894
DO - 10.1109/IROS47612.2022.9981894
M3 - Conference contribution
AN - SCOPUS:85146329413
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 11570
EP - 11577
BT - 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022
Y2 - 23 October 2022 through 27 October 2022
ER -