Implementation of an autonomous mobile robot with semantic segmentation, object detection, motion planning and control systems
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Updated
Sep 20, 2023 - Jupyter Notebook
Implementation of an autonomous mobile robot with semantic segmentation, object detection, motion planning and control systems
ROS-Noetic-based autonomous driving simulation project , using DWA path planning algorithm and dual PID controller
[ZJU Robotics Project] DWA and Astar algorithms for wheeled-robot path planning
The Dynamic Window Approach (DWA) planning algorithm written in C with Python Bindings
AUTONOMOUS ROBOT NAVIGATION USING ROS Clearpath Husky A200 robot with Gazebo and RViz simulations using different SLAM and Path Planning algorithms. 360 degrees laser scan with two SICK LMS511 LIDARs
Heavy rainfall intensity as a function of duration and return period is defined according to DWA-A 531 (2012). This program reads rainfall measurement data and calculates the distribution of design rainfall as a function of both return period and duration, for durations up to 12 hours (and beyond) and return periods in the range 0.5 a ≤ Tₙ ≤ 100 a.
Local Planner for ROS2
Simulation for DWA (Dynamic Window Approach) and modified DWA algorithms
This work investigates automatic hyperparameter tuning for planners such as DWA and TEB, and our navigation framework LE-Nav can be used to adjust hyperparameters of any optimization-based planner.
The local planner used in our paper 'ODS-Bot: Mobile Robot Navigation for Outdoor Delivery Services' @ IEEE Access'22
Multi-Task Learning for Accelerated MR Reconstruction
This repo is multi-robot motion planner framework which uses CCBS as a global planner to determine non-collision paths for all robots. The paths are sent to local planners which determine the path segment for robots to follow. The packages work on ROS and Gazebo.
Multi-task learning with adapted torchvision models (SSD, FasterRCNN, DeepLabv3) using Lightning-AI
A 2D navigation metapackage for AMR (Autonomous Mobile Robot)
Complete ROS2 navigation and exploration system with multiple advanced algorithms: - Bidirectional A* path planning - DWA local planner for real-time obstacle avoidance - RRT exploration strategy - PID motion control - Comprehensive English documentation - Performance optimization guidelines - GitHub-ready project structure
Simulated and analyzed different path planning algorithms such as DWA and Dijkstra in a custom world modeled in Autodesk Fusion 360. The modeled world was imported to Gazebo, and the paths planned by turtlebot3 were visualized in Rviz.
The local planning algorithm for the Mirte Master robot.
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