COVID surveillance robot: Monitoring social distancing constraints in indoor scenarios
Observing social/physical distancing norms between humans has become an indispensable
precaution to slow down the transmission of COVID-19. We present a novel method to …
precaution to slow down the transmission of COVID-19. We present a novel method to …
Drl-vo: Learning to navigate through crowded dynamic scenes using velocity obstacles
This article proposes a novel learning-based control policy with strong generalizability to
new environments that enables a mobile robot to navigate autonomously through spaces …
new environments that enables a mobile robot to navigate autonomously through spaces …
Intention aware robot crowd navigation with attention-based interaction graph
We study the problem of safe and intention-aware robot navigation in dense and interactive
crowds. Most previous reinforcement learning (RL) based methods fail to consider different …
crowds. Most previous reinforcement learning (RL) based methods fail to consider different …
Dwa-rl: Dynamically feasible deep reinforcement learning policy for robot navigation among mobile obstacles
U Patel, NKS Kumar, AJ Sathyamoorthy… - … on Robotics and …, 2021 - ieeexplore.ieee.org
We present a novel Deep Reinforcement Learning (DRL) based policy to compute
dynamically feasible and spatially aware velocities for a robot navigating among mobile …
dynamically feasible and spatially aware velocities for a robot navigating among mobile …
Frozone: Freezing-free, pedestrian-friendly navigation in human crowds
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 …
arises when a robot navigates through dense scenarios and crowds. Our method senses …
Autonomous ground navigation in highly constrained spaces: Lessons learned from the benchmark autonomous robot navigation challenge at icra 2022 [competitions …
The Benchmark Autonomous Robot Navigation (BARN) Challenge took place at the 2022
IEEE International Conference on Robotics and Automation (ICRA), in Philadelphia, PA …
IEEE International Conference on Robotics and Automation (ICRA), in Philadelphia, PA …
Land: Learning to navigate from disengagements
Consistently testing autonomous mobile robots in real world scenarios is a necessary aspect
of developing autonomous navigation systems. Each time the human safety monitor …
of developing autonomous navigation systems. Each time the human safety monitor …
From crowd motion prediction to robot navigation in crowds
S Poddar, C Mavrogiannis… - 2023 IEEE/RSJ …, 2023 - ieeexplore.ieee.org
We focus on robot navigation in crowded environments. To navigate safely and efficiently
within crowds, robots need models for crowd motion prediction. Building such models is …
within crowds, robots need models for crowd motion prediction. Building such models is …
Robot navigation in a crowd by integrating deep reinforcement learning and online planning
Navigating mobile robots along time-efficient and collision-free paths in crowds is still an
open and challenging problem. The key is to build a profound understanding of the crowd …
open and challenging problem. The key is to build a profound understanding of the crowd …
Navigating robots in dynamic environment with deep reinforcement learning
In the fight against COVID-19, many robots replace human employees in various tasks that
involve a risk of infection. Among these tasks, the fundamental problem of navigating robots …
involve a risk of infection. Among these tasks, the fundamental problem of navigating robots …