55 citations · 99 across the 22 of their papers we have counts for
23 papers
TOPGN: Real-time Transparent Obstacle Detection using Lidar Point Cloud Intensity for Autonomous Robot Navigation
Kasun Weerakoon, Adarsh Jagan Sathyamoorthy, Mohamed Elnoor +2
We present TOPGN, a novel method for real-time transparent obstacle detection for robot navigation in unknown environments. We use a multi-layer 2D grid map representation obtained…
CoNVOI: Context-aware Navigation using Vision Language Models in Outdoor and Indoor Environments
Adarsh Jagan Sathyamoorthy, Kasun Weerakoon, Mohamed Elnoor +6
We present ConVOI, a novel method for autonomous robot navigation in real-world indoor and outdoor environments using Vision Language Models (VLMs). We employ VLMs in two ways: fir…
AMCO: Adaptive Multimodal Coupling of Vision and Proprioception for Quadruped Robot Navigation in Outdoor Environments
Mohamed Elnoor, Kasun Weerakoon, Adarsh Jagan Sathyamoorthy +3
We present AMCO, a novel navigation method for quadruped robots that adaptively combines vision-based and proprioception-based perception capabilities. Our approach uses three cost…
AdVENTR: Autonomous Robot Navigation in Complex Outdoor Environments
Kasun Weerakoon, Adarsh Jagan Sathyamoorthy, Mohamed Elnoor +1
We present a novel system, AdVENTR for autonomous robot navigation in unstructured outdoor environments that consist of uneven and vegetated terrains. Our approach is general and c…
Using Lidar Intensity for Robot Navigation
Adarsh Jagan Sathyamoorthy, Kasun Weerakoon, Mohamed Elnoor +1
We present Multi-Layer Intensity Map, a novel 3D object representation for robot perception and autonomous navigation. Intensity maps consist of multiple stacked layers of 2D grid…
VAPOR: Legged Robot Navigation in Outdoor Vegetation Using Offline Reinforcement Learning
Kasun Weerakoon, Adarsh Jagan Sathyamoorthy, Mohamed Elnoor +1
We present VAPOR, a novel method for autonomous legged robot navigation in unstructured, densely vegetated outdoor environments using offline Reinforcement Learning (RL). Our metho…
MTG: Mapless Trajectory Generator with Traversability Coverage for Outdoor Navigation
Jing Liang, Peng Gao, Xuesu Xiao +4
We present a novel learning-based trajectory generation algorithm for outdoor robot navigation. Our goal is to compute collision-free paths that also satisfy the environment-specif…
ProNav: Proprioceptive Traversability Estimation for Legged Robot Navigation in Outdoor Environments
Mohamed Elnoor, Adarsh Jagan Sathyamoorthy, Kasun Weerakoon +1
We propose a novel method, ProNav, which uses proprioceptive signals for traversability estimation in challenging outdoor terrains for autonomous legged robot navigation. Our appro…
Confidence-Controlled Exploration: Efficient Sparse-Reward Policy Learning for Robot Navigation
Bhrij Patel, Kasun Weerakoon, Wesley A. Suttle +5
Reinforcement learning (RL) is a promising approach for robotic navigation, allowing robots to learn through trial and error. However, real-world robotic tasks often suffer from sp…
CrossLoc3D: Aerial-Ground Cross-Source 3D Place Recognition
Tianrui Guan, Aswath Muthuselvam, Montana Hoover +5
We present CrossLoc3D, a novel 3D place recognition method that solves a large-scale point matching problem in a cross-source setting. Cross-source point cloud data corresponds to…
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…
HTRON:Efficient Outdoor Navigation with Sparse Rewards via Heavy Tailed Adaptive Reinforce Algorithm
Kasun Weerakoon, Souradip Chakraborty, Nare Karapetyan +3
We present a novel approach to improve the performance of deep reinforcement learning (DRL) based outdoor robot navigation systems. Most, existing DRL methods are based on carefull…
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…
TerraPN: Unstructured Terrain Navigation using Online Self-Supervised Learning
Adarsh Jagan Sathyamoorthy, Kasun Weerakoon, Tianrui Guan +2
We present TerraPN, a novel method that learns the surface properties (traction, bumpiness, deformability, etc.) of complex outdoor terrains directly from robot-terrain interaction…
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…
GANav: Efficient Terrain Segmentation for Robot Navigation in Unstructured Outdoor Environments
Tianrui Guan, Divya Kothandaraman, Rohan Chandra +3
We propose GANav, a novel group-wise attention mechanism to identify safe and navigable regions in off-road terrains and unstructured environments from RGB images. Our approach cla…
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…
DenseCAvoid: Real-time Navigation in Dense Crowds using Anticipatory Behaviors
Adarsh Jagan Sathyamoorthy, Jing Liang, Utsav Patel +3
We present DenseCAvoid, a novel navigation algorithm for navigating a robot through dense crowds and avoiding collisions by anticipating pedestrian behaviors. Our formulation uses…
LSwarm: Efficient Collision Avoidance for Large Swarms with Coverage Constraints in Complex Urban Scenes
Senthil Hariharan Arul, Adarsh Jagan Sathyamoorthy, Shivang Patel +4
In this paper, we address the problem of collision avoidance for a swarm of UAVs used for continuous surveillance of an urban environment. Our method, LSwarm, efficiently avoids co…