Lists (13)
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Stars
sources for object or obstacle detection utilizing individual 2D LiDAR on each stationary robot
C++ implementation to Detect, track and classify multiple objects using LIDAR scans or point cloud
Detection and Tracking of Moving Objects with 2D LIDAR
An obstacle tracking ROS package for detecting obstacles using 2D LiDAR scan using an Extended object tracking algorithm
Use Kalman Filter and Hungarian algorithm to do tracking work based on 2D Lidar dataset of KITTI dataset
Detection and Tracking of Moving Objects (DATMO) using sensor_msgs/Lidar.
Gaussian Process-based Traversability Analysis for Terrain Mapless Navigation (ICRA 2024)
BiC-MPPI: Goal-Pursuing, Sampling-Based Bidirectional Rollout Clustering Path Integral for Trajectory Optimization
Implementation of the paper "Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning"
Ultra-Fast line segment extraction using Douglas-Peucker algorithm. Works with ROS1.
This is an implementation of ROS Local Planner using the Dijkstra's algorithm and the Hybrid A star algorithm
Simple 2D lidar simulator and obstacle clustering
Simulate dynamic environments and LiDAR observations
Spiritual successor to ros-planning/navigation.
Code for the IEEE Robotics and Automation Letters paper titled "Multi-Modal MPPI and Active Inference for Reactive Task and Motion Planning"
off-road navigation simulator for benchmarking planning algorithms
This project addresses navigation in crowded environments by integrating goal-conditioned generative models with Sampling-based Model Predictive Control (SMPC).
Code for the paper "Towards a Safe Real-Time Motion Planning Framework for Autonomous Driving Systems: An MPPI Approach"
The reimplementation of Model Predictive Path Integral (MPPI) from the paper "Information Theoretic MPC for Model-Based Reinforcement Learning" (Williams et al., 2017) for the pendulum OpenAI Gym e…
A ROS package of a autonomous navigation method based on SAC and Bidirectional RRT* (Repository RL-RRT-Global-Planner).
[ICML 2023] Variational Curriculum Reinforcement Learning for Unsupervised Discovery of Skills
[ICRA 2023] Adaptive and Explainable Deployment of Navigation Skills via Hierarchical Deep Reinforcement Learning
Regularized Reinforcement Learning for Improved Classical Motion Planning with Safety Modules
Evaluating pre-trained navigation agents under corruptions
Projection Guided Sampling-Based Optimization For Autonomous Navigation