55 citations · 87 across the 7 of their papers we have counts for
8 papers
GrASPE: Graph based Multimodal Fusion for Robot Navigation in Unstructured Outdoor Environments
Kasun Weerakoon, Adarsh Jagan Sathyamoorthy, Jing Liang +3
We present a novel trajectory traversability estimation and planning algorithm for robot navigation in complex outdoor environments. We incorporate multimodal sensory inputs from a…
TERP: Reliable Planning in Uneven Outdoor Environments using Deep Reinforcement Learning
Kasun Weerakoon, Adarsh Jagan Sathyamoorthy, Utsav Patel +1
We present a novel method for reliable robot navigation in uneven outdoor terrains. Our approach employs a novel fully-trained Deep Reinforcement Learning (DRL) network that uses e…
CoMet: Modeling Group Cohesion for Socially Compliant Robot Navigation in Crowded Scenes
Adarsh Jagan Sathyamoorthy, Utsav Patel, Moumita Paul +3
We present CoMet, a novel approach for computing a group's cohesion and using that to improve a robot's navigation in crowded scenes. Our approach uses a novel cohesion-metric that…
Dynamically Feasible Deep Reinforcement Learning Policy for Robot Navigation in Dense Mobile Crowds
Utsav Patel, Nithish Kumar, Adarsh Jagan Sathyamoorthy +1
We present a novel Deep Reinforcement Learning (DRL) based policy to compute dynamically feasible and spatially aware velocities for a robot navigating among mobile obstacles. Our…
COVID-Robot: Monitoring Social Distancing Constraints in Crowded Scenarios
Adarsh Jagan Sathyamoorthy, Utsav Patel, Yash Ajay Savle +2
Maintaining social distancing norms between humans has become an indispensable precaution to slow down the transmission of COVID-19. We present a novel method to automatically dete…
Realtime Collision Avoidance for Mobile Robots in Dense Crowds using Implicit Multi-sensor Fusion and Deep Reinforcement Learning
Jing Liang, Utsav Patel, Adarsh Jagan Sathyamoorthy +1
We present a novel learning-based collision avoidance algorithm, CrowdSteer, for mobile robots operating in dense and crowded environments. Our approach is end-to-end and uses mult…