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Scalable Co-optimization of Collective Robotic Mobility and the Artificial Environment

Project description

Paving the way for an environment conducive to robotic mobility

Autonomous agents – such as robots and driverless cars – need to collaborate and cooperate when they are working together in shared spaces, such as warehouses or traffic systems. But to make progress in this area, we need to stop trying to shoehorn the robot mobility systems of the future into the transport environments of the past. Up to now, there has been a disconnect between the optimisation of mobile robots and their immediate environment. The EU-funded gAIa project will study this environment, which is as much a variable as the robot itself. By identifying more conducive and efficient environments, the project will help improve collective robot policies. The findings will impact transport planning and urban design, facilitating a new path towards mobile vehicles that are connected and coordinated. Overall, the project’s aim is to shed light on the coupling between environmental structure and collective robotic mobility.

Objective

The behavior of intelligent systems, both living and artificial, is influenced through the structure of their surrounding environment. In nature, environmental constraints dictate the creation, unfolding, and interaction of living beings. Living systems are prototypes for collective robot behaviors— yet, despite the obvious influence of spatial constraints on interactions, the optimization of mobile robots and their immediate environment has been disjoint. Little thought has been given to what would make an artificial environment conducive to effective and efficient collective robotic mobility.

The premise of this project is that the environment is as much a variable as the robot itself. I want to expose the coupling between environmental structure and collective robotic mobility. In pursuit of this goal, I propose a co-optimization scheme that finds the best robot-environment pairs in an automated, scalable manner. The work in this project will (i) optimize control policies that define the behavior of collective mobile robot systems, and (ii) find environments that are more conducive to efficient coordination and cooperation. The developed techniques will allow us to perform first-of-a-kind analyses that would reveal novel environmental paradigms and the collective robot policies optimized around them. Ultimately, this project will spearhead new ways of thinking about transport planning and urban design, in the wake of a new generation of mobile vehicles that are connected and coordinated.

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Coordinator

THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
Net EU contribution
€ 1 495 338,00
Address
Trinity lane the old schools
CB2 1TN Cambridge
United Kingdom

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Region
East of England East Anglia Cambridgeshire CC
Activity type
Higher or Secondary Education Establishments
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Other funding
€ 0,00

Beneficiaries (1)