15 citations · 20 across the 5 of their papers we have counts for
8 papers
Effects of Controller Heterogeneity on Autonomous Vehicle Traffic
Matthew Le Maitre, Amanda Prorok
Interactions between road users are both highly non-linear and profoundly complex, and there is no reason to expect that interactions between autonomous vehicles will be any differ…
Mobile Robot Path Planning in Dynamic Environments through Globally Guided Reinforcement Learning
Binyu Wang, Zhe Liu, Qingbiao Li +1
Path planning for mobile robots in large dynamic environments is a challenging problem, as the robots are required to efficiently reach their given goals while simultaneously avoid…
Graph Neural Networks for Decentralized Multi-Robot Path Planning
Qingbiao Li, Fernando Gama, Alejandro Ribeiro +1
Effective communication is key to successful, decentralized, multi-robot path planning. Yet, it is far from obvious what information is crucial to the task at hand, and how and whe…
Multi-Vehicle Mixed-Reality Reinforcement Learning for Autonomous Multi-Lane Driving
Rupert Mitchell, Jenny Fletcher, Jacopo Panerati +1
Autonomous driving promises to transform road transport. Multi-vehicle and multi-lane scenarios, however, present unique challenges due to constrained navigation and unpredictable…
An Adversarial Approach to Private Flocking in Mobile Robot Teams
Hehui Zheng, Jacopo Panerati, Giovanni Beltrame +1
Privacy is an important facet of defence against adversaries. In this letter, we introduce the problem of private flocking. We consider a team of mobile robots flocking in the pres…
Multi-Robot Path Deconfliction through Prioritization by Path Prospects
Wenying Wu, Subhrajit Bhattacharya, Amanda Prorok
This work deals with the problem of planning conflict-free paths for mobile robots in cluttered environments. Since centralized, coupled planning algorithms are computationally int…