Jiří Horyna presents Robot Swarms Adapt Better to Localization Dropouts Then a Single Robot
On 2025-09-09 - 2025-09-09 11:00:00 at E112, Karlovo náměstí 13, Praha 2
In this paper, we present the Swarming Without an Anchor (SWA) approach to
state
estimation in swarms of Unmanned Aerial Vehicles (UAVs) experiencing
ego-localization dropout, where individual agents are laterally stabilized
using
relative information only. We propose to fuse decentralized state estimation
with robust mutual perception and onboard sensor data to maintain accurate
state
awareness despite intermittent localization failures. Thus, the relative
information used to estimate the lateral state of UAVs enables the
identification of the unambiguous state of UAVs with respect to the local
constellation. The resulting behavior reaches velocity consensus, as this task
can be referred to as the double integrator synchronization problem. All
disturbances and performance degradations except a uniform translation drift of
the swarm as a whole is attenuated which is enabling new opportunities in using
tight cooperation for increasing reliability and resilience of multi-UAV
systems. Simulations and real-world experiments validate the effectiveness of
our approach, demonstrating its capability to sustain cohesive swarm behavior
in
challenging conditions of unreliable or unavailable primary localization.
The seminar will be held in a short format of 20 minutes + 10 minutes Q&A.
References:
Jiri Horyna, Roland Jung, Stephan Weiss, Eliseo Ferrante and Martin Saska.
Swarming Without an Anchor (SWA): Robot Swarms Adapt Better to Localization
Dropouts Then a Single Robot. IEEE Robotics and Automation Letters
10():6207–6214, June 2025.
Paper: https://ieeexplore.ieee.org/abstract/document/10971233
Video: https://youtu.be/kPiOdsPKh-U?si=EIbENJ6CQmueZ8BR
state
estimation in swarms of Unmanned Aerial Vehicles (UAVs) experiencing
ego-localization dropout, where individual agents are laterally stabilized
using
relative information only. We propose to fuse decentralized state estimation
with robust mutual perception and onboard sensor data to maintain accurate
state
awareness despite intermittent localization failures. Thus, the relative
information used to estimate the lateral state of UAVs enables the
identification of the unambiguous state of UAVs with respect to the local
constellation. The resulting behavior reaches velocity consensus, as this task
can be referred to as the double integrator synchronization problem. All
disturbances and performance degradations except a uniform translation drift of
the swarm as a whole is attenuated which is enabling new opportunities in using
tight cooperation for increasing reliability and resilience of multi-UAV
systems. Simulations and real-world experiments validate the effectiveness of
our approach, demonstrating its capability to sustain cohesive swarm behavior
in
challenging conditions of unreliable or unavailable primary localization.
The seminar will be held in a short format of 20 minutes + 10 minutes Q&A.
References:
Jiri Horyna, Roland Jung, Stephan Weiss, Eliseo Ferrante and Martin Saska.
Swarming Without an Anchor (SWA): Robot Swarms Adapt Better to Localization
Dropouts Then a Single Robot. IEEE Robotics and Automation Letters
10():6207–6214, June 2025.
Paper: https://ieeexplore.ieee.org/abstract/document/10971233
Video: https://youtu.be/kPiOdsPKh-U?si=EIbENJ6CQmueZ8BR