Robot Navigation with Dynamics Planning
Advanced navigation strategies for dynamic environments
Project Overview
This project focuses on developing advanced robot navigation strategies using decremental dynamics planning, enabling robots to efficiently navigate in dynamic environments with changing obstacles and goals.
Technical Implementation
Navigation Architecture
- Decremental Planning: Efficient replanning strategy that reuses previous computations
- Dynamic Obstacle Handling: Real-time adaptation to moving obstacles
- Goal Switching: Seamless transition between multiple navigation goals
- Path Optimization: Continuous refinement of navigation trajectories
Results and Impact
- Planning Efficiency: 60% reduction in replanning time
- Navigation Success: 95% success rate in dynamic environments
- Path Quality: 25% shorter paths compared to baseline methods
Technical Stack
- Framework: ROS2 with custom planning modules
- Simulation: Gazebo and IsaacSim for testing
- Visualization: RViz for path visualization
- Deployment: Real-time implementation on mobile robots
Code and Demo
GitHub Repository | Paper |