[TRO 2025] NeuPAN: Direct Point Robot Navigation with End-to-End Model-based Learning.
Motion Planner for Self Driving Cars
An all-in-one application to visualize multiple different local path planning algorithms
A PAL Mobile Base for your advanced navigation needs
A simple planner that attempts to keep the robot close to a line between the starting and target goal. Doubles as a demo backend for Vizanti
Model Predictive Control (MPC) based waypoint tracking controller (ROS navigation stack local planner plugin)
Gymnasium-based social navigation simulation and benchmarking for a robot moving through pedestrian-filled environments.
This package provides functionality for teaching and repeating (Teach and Repeat) navigation paths using ROS 2.
A custom-built **Dynamic Window Approach (DWA) local planner** for TurtleBot3 in **ROS2 Humble**, designed to work in Gazebo simulation. It computes real-time velocity commands using laser scan and odometry data, visualizes evaluated trajectories in RViz2, and operates without relying on Nav2 plugins.
Adaptive-clearance local controller for ROS 2 Nav2, balancing obstacle clearance with narrow-passage traversal.
Continuous Curvature Path Generator based on 3D Waypoints
Nav2-native MPPI local controller for ROS 2 Jazzy: online local-minima detection-and-escape + a dynamic-obstacle CBF safety filter that preserves forward invariance under stated conditions. Ships the preprint, a 1,200-trial randomized 2D benchmark with raw artifacts, and a Gazebo U-trap testbed.
Mobile Robot Navigation using Dynamic Webs
Obstacle avoidance using data from depth camera and lidar
Custom ROS2 DWA local planner with real-time trajectory sampling, obstacle avoidance, recovery logic, and RViz visualization — built from scratch without Nav2, for semi-structured real-world environments.
Dynamic-obstacle avoidance local planner: real-time perception & motion prediction, kinodynamic replanning, and provably safe model-predictive control. One command brings up the full pipeline; set goals directly in RViz.
robot navigation, you can receive goal, then make global/local plan to the goal. include trajectory, obstacle and velocity.
Reproducibility package for benchmarking five ROS-based local planners with TurtleBot3 Burger in Gazebo using ROS Noetic.
Aisle-Centring Timed Elastic Band (AC-TEB), an extension of the TEB model predictive controller that drives the robot along the aisle centreline using a single low-cost depth camera.
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