activity
20182026
most citedCoCo Games: Graphical Game-Theoretic Swarm Control for Communication-Aware Coverage

10 citations · 38 across the 34 of their papers we have counts for

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Showing 2022Show all

7 papers · 1 filter

cs.RO2022

Uncertainty-Aware Online Merge Planning with Learned Driver Behavior

Liam A. Kruse, Esen Yel, Ransalu Senanayake +1

Safe and reliable autonomy solutions are a critical component of next-generation intelligent transportation systems. Autonomous vehicles in such systems must reason about complex a…

cs.LG2022

Renaissance Robot: Optimal Transport Policy Fusion for Learning Diverse Skills

Julia Tan, Ransalu Senanayake, Fabio Ramos

Deep reinforcement learning (RL) is a promising approach to solving complex robotics problems. However, the process of learning through trial-and-error interactions is often highly…

cs.LG2022★ 9 cited

Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning

Bertrand Charpentier, Ransalu Senanayake, Mykel Kochenderfer +1

Characterizing aleatoric and epistemic uncertainty on the predicted rewards can help in building reliable reinforcement learning (RL) systems. Aleatoric uncertainty results from th…

cs.RO2022

Graphical Games for UAV Swarm Control Under Time-Varying Communication Networks

Malintha Fernando, Ransalu Senanayake, Ariful Azad +1

We propose a unified framework for coordinating Unmanned Aerial Vehicle (UAV) swarms operating under time-varying communication networks. Our framework builds on the concept of gra…

cs.RO2022

How Do We Fail? Stress Testing Perception in Autonomous Vehicles

Harrison Delecki, Masha Itkina, Bernard Lange +2

Autonomous vehicles (AVs) rely on environment perception and behavior prediction to reason about agents in their surroundings. These perception systems must be robust to adverse we…

cs.RO2022

FIG-OP: Exploring Large-Scale Unknown Environments on a Fixed Time Budget

Oriana Peltzer, Amanda Bouman, Sung-Kyun Kim +8

We present a method for autonomous exploration of large-scale unknown environments under mission time constraints. We start by proposing the Frontloaded Information Gain Orienteeri…