55 citations · 88 across the 7 of their papers we have counts for
8 papers
Sim-to-Real Strategy for Spatially Aware Robot Navigation in Uneven Outdoor Environments
Kasun Weerakoon, Adarsh Jagan Sathyamoorthy, Dinesh Manocha
Deep Reinforcement Learning (DRL) is hugely successful due to the availability of realistic simulated environments. However, performance degradation during simulation to real-world…
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…
Frozone: Freezing-Free, Pedestrian-Friendly Navigation in Human Crowds
Adarsh Jagan Sathyamoorthy, Utsav Patel, Tianrui Guan +1
We present Frozone, a novel algorithm to deal with the Freezing Robot Problem (FRP) that arises when a robot navigates through dense scenarios and crowds. Our method senses and exp…