| On 2023-06-09 at (Brussels Time) |
Abstract
Collective decision-making is an essential capability of large-scale multi-robot systems to establish autonomy on the swarm level. We assign a decentralized robot system with the task of exploring an unbounded environment, finding consensus on the mean of a measurable environmental feature, and aggregating at areas where that value is measured (e.g., a contour line). A unique quality of this task is a causal loop between the robots' dynamic network topology and their decision-making. For example, the network's mean node degree influences time to convergence while the currently agreed-on mean value influences the swarm's aggregation location, hence, also the network structure as well as the precision error. Short Bio of the Speaker
Mohsen is a doctoral researcher at the excellence cluster "Science of Intelligence" where he works on Project 27 titled “Speed-Accuracy Tradeoffs in Collective Estimation”, under the supervision of Pawel Romanczuk and Heiko Hamann. He received his Master’s degree in Dynamics and Control with a study on state estimation of nonlinear systems using a swarm-based optimization algorithm. His research is mainly focused on collective intelligence, swarm robotics, and network dynamics.
