Popular GitHub Repositories for Collision Avoidance

[ICRA19] Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning

ROS package for dynamic obstacle avoidance for ground robots trained with deep RL

[IEEE RA-L'25] NavRL: Learning Safe Flight in Dynamic Environments (NVIDIA Isaac/Python/ROS1/ROS2)

Implementation of the paper "Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning"

[T-RO 2023] DRL-VO: Learning to Navigate Through Crowded Dynamic Scenes Using Velocity Obstacles

[ICRA 2023] Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph

LV-DOT: LiDAR-Visual Dynamic Obstacle Detection and Tracking (C++/Python/ROS)

[IROS20] Relational graph learning for crowd navigation

A multi agent path planning solution under a warehouse scenario using Q learning and transfer learning.??

Training code for GA3C-CADRL algorithm (collision avoidance with deep RL)

Mapless Collision Avoidance of Turtlebot3 Mobile Robot Using DDPG and Prioritized Experience Replay

[ICRA 2021] Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement Learning

[ICRA 2023] Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph -- Sim2real code on Turtlebot2i

[arXiv 2024] "HEIGHT: Heterogeneous Interaction Graph Transformer for Robot Navigation in Crowded and Constrained Environments"

A hybrid collision avoidance system combining Deep Reinforcement Learning with Model Predictive Control, designed for autonomous vehicles in CARLA to navigate scenarios with stationary obstacles.

Autonomous racing using ILQR and JAX.

An end-to-end (E2E) reinforcement learning model for autonomous vehicle collision avoidance in the CARLA simulator, using a recurrent PPO algorithm for dynamic control. The model processes RGB camera inputs to make real-time acceleration and steering decisions.

Tello AI features. Face recognition and tracking, collision avoidance, reinforcement learning and more.

A robot(boat) that autonomously navigate with the optimal path and obstacle avoidance through deep reinforcement learning is being produced.

Keypoint Tracking and Matching in Autonomous Vehicles to measure TTC between consecutive frames of the KITTI Dataset