Swarm Mini-Workshop

Am 8. August 2022 um 14:00 Uhr im Raum "Von Neumann" (R. 2.132, Geb. 64, 2.OG)

Der Swarm Mini-Workshop beginnt um 14:00 Uhr und beinhaltet 3 Vorträge, die jeweils ca. eine Stunde dauern.


1. Vortrag (14:00):

Speaker: Dr. Andreagiovanni Reina

Title: When less is more — how to improve the swarm performance by reducing the robots' capabilities

Most of our experiences, as well as our intuition, are usually built on a linear understanding of systems and processes. Complex systems in general, and more specifically swarm robotics in this context, leverage non-linear effects to self-organise and to ensure that 'more is different'. Our study shows the nonlinear and hence counter-intuitive effect of 'less is more' in two scenarios of collective decision making, site selection and collective perception. Although it seems intuitive that being able to communicate over longer distances should be beneficial, swarms were found to sometimes profit from communication limitations. Our findings are supported by a mean-field model, an exhaustive set of multiagent simulations, and experiments with 50 Kilobot robots. Our research shows that limiting the communication to a local neighbourhood is a cheap decentralised solution to allow robot swarms to adapt to previously unknown information that is locally observed by a minority of the robots. Studying this effect also find an additional effect that we call 'slower is faster': in certain situations, swarms benefit from sampling their environment less frequently. While intrigued by this result, we did not manage to explain it, Yet!

Short Bio of the Speaker:
Andreagiovanni Reina received an MSc degree in Computer Engineering from Politecnico di Milano, Italy, and a PhD degree in applied sciences from IRIDIA, Universite Libre de Bruxelles, Belgium. He is a research fellow in collective behaviour at the Interdisciplinary Institute for Artificial Intelligence (IRIDIA), Universite Libre de Bruxelles, funded by the Belgian F.R.S.-FNRS as a Charge de Recherches. He was a research fellow at the University of Sheffield, UK, from 2015 to 2020. He has been a researcher in six European projects on distributed robotic systems since 2009.


2. Vortrag (15:00):

Speaker: Dr. Aaron Becker

Title: Pursuit and evasion for a swarm under high stakes

The proliferation of inexpensive remotely controlled drones makes large drone swarms a near possibility. Swarms of drones can be useful for overwhelming defensive positions and then loitering in hostile areas near potential adversaries. The pursuit-evasion problem that arises from the need to engage each drone in the swarm in an efficient way and subject to constraints is an example of a Traveling Salesman Problem with Time Windows.
A defending turret must visit each attacking drone in the swarm once, as quickly as possible to counter the threat. This constitutes a Shortest Hamiltonian Path through the swarm subject to the time constraints of visiting each drone before it can reach the defending turret. Finding this path is made more difficult when the swarm can alter its configuration, changing the relative distances between drones. The rapid pace of engagement, computational complexity, and changing constraints makes optimal solvers infeasible. Instead, it is reasonable to pursue a mixed strategy of heuristic approaches able to solve the online problem and select a near-best path through the attacking drones.

Short Bio of the Speaker:
Aaron is an Associate Prof. in Electrical & Computer Engineering at the University of Houston. As a NSF '16 CAREER & Alexander von Humboldt Fellowship recipient, his lab manipulates micro-scale swarms with magnetic fields, navigates robotic tools using medical MRIs, kills mosquitos with drones, searches for oil, and assembles structures with swarms.
During his position as a Research Fellow with Boston Children's Hospital & Harvard Medical School, he implemented robotics powered and controlled by the magnetic field of an MRI. As a Rice University Postdoc in the Multi-Robot Systems Lab, Aaron investigated control of distributed systems and nanorobotics with experts in the fields. Aaron earned his PhD in Electrical & Computer Engineering at the University of Illinois at Urbana-Champaign.


3. Vortrag (16:00):

Speaker: Dr. Andreagiovanni Reina

Title: Economics-inspired swarm robotics

Robot swarms are generally considered to be composed of cooperative agents that, despite their limited individual capabilities, can perform difficult tasks by working together. However, in open swarms, where different robots can be added to the swarm by different parties with potentially competing interests, cooperation is but one of many strategies. We envision an information market where robots can buy and sell information through transactions stored on a distributed blockchain, and where cooperation is encouraged by the economy itself. As a proof of concept, we study a classical foraging task, where exchanging information with other robots is paramount to accomplish the task efficiently. We illustrate that even a single Byzantine robot that lies to others can heavily disrupt the swarm. Hence, we devise two protection mechanisms. Through an individual-level protection mechanism, robots are more sceptical about others’ information and can detect and discard Byzantine information, at the cost of lower efficiency. Through a systemic protection mechanism based on economic rules regulating robot interactions, robots that sell honest information acquire over time more wealth than Byzantines selling false information. Our simulations show that a well-designed robot economy penalises misinformation spreading and protects the swarm from Byzantine behaviour. We believe this research can pave the way for economic-based swarm robotics exploiting the timely opportunity for decentralised economies offered by blockchain technology.


Donnerstag, 21.07.2022 15:17