Project description
Controlling emergent behaviours of robot swarms
Robot swarms are sensitive to imperfections, making it challenging to design and control them. Even tiny imperfections can amplify across large numbers of robots, undermining their overall performance. Imperfections may also lead to complex emergent behaviours, such as intricate trajectory patterns. The ERC-funded iSwarm project proposes a new approach to control emergent behaviours. Instead of suppressing imperfections, the idea is to embrace and use them as novel distributed control inputs. This requires a fresh perspective on analysing algorithms and integrating robots for multi-agent systems, focusing on the intersection of algebraic graph theory, network theory, control, and mechatronics. Ultimately, a framework to evaluate emergent behaviours with imperfect inputs will be developed.
Objective
Robot swarms are incredibly fragile against imperfections. World-class roboticists agree that one of the fundamental challenges in robotics is on the availability of systematic methods with formal guarantees for the design and control of the swarm's force multiplication, where sensing, actuation, and communication are distributed in space. However, no matter the approach, control theory, or heuristic, tiny imperfections are amplified throughout large numbers of robots and rapidly erode and make unpredictable the overall performance of the swarm. Notwithstanding, imperfections can result in surprising complex emergent behaviors such as intricate trajectory patterns of mobile robot swarms.
iSwarm questions the current paradigm of fighting imperfections to suppress their “damaging” effects. Conversely, I propose a rigorous control theory to unleash and ally with imperfections, such as dropouts, delays, and scaling/biasing factors in sensors and actuators, as novel distributed control inputs for taming emergent behaviors. My paradigm shift requires new ways of analyzing algorithms and their robot integration at the crossroads between algebraic graph theory, network theory, control, and mechatronics for multi-agent systems.
To achieve the project's goal, I will: 1) develop a general formulation to characterize the controllability/stabilizability of emergent behaviors with imperfections as inputs; 2) introduce unconventional strategies such as the mismatched Lyapunov functions to engineer emergent behaviors; 3) construct equivalence principles between imperfections and inconsistent shared information to improve the effectiveness of the swarm’s “collective awareness” for fault-recovery algorithms; and 4) demonstrate the control of a state-of-the-art robot swarm in non-lab conditions by exploiting robot imperfections.
iSwarm regards imperfections as part of the solution, will inspire innovative research methods and lead new applications of multi-robot systems.
Fields of science
- engineering and technologymechanical engineeringmechatronics
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringroboticsswarm robotics
- natural sciencesmathematicspure mathematicsdiscrete mathematicsgraph theory
- natural sciencescomputer and information sciencesartificial intelligenceheuristic programming
Keywords
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Topic(s)
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
18071 Granada
Spain