rda_ros

rda_ros is the ROS Wrapper for the RDA Planner, enabling seamless integration of RDA into ROS-based robotic systems. This wrapper provides a ROS interface for RDA, allowing users to easily configure and interact with the planner through ROS topics and services. By leveraging the ROS ecosystem, RDA-ROS simplifies the deployment and utilization of the RDA Planner in ROS-based robotic applications.

Below is our demonstrations of RDA-ROS in a simulated environment using Gazebo for dynamic collision avoidance and CARLA for autonomous driving:

RDA Planner is a high-performance, optimization-based, Model Predictive Control (MPC) motion planner designed for autonomous navigation in complex and cluttered environments. Utilizing the Alternating Direction Method of Multipliers (ADMM), RDA decomposes complex optimization problems into several simple subproblems. This decomposition enables parallel computation of collision avoidance constraints for each obstacle, significantly enhancing computation speed.

Key Features:

• Shape-Aware Planning: Handles robots and obstacles with arbitrary convex shapes, ensuring versatility across diverse scenarios.
• High-Precision Control: Achieves accurate control trajectories through advanced optimization solvers, enhancing navigation reliability.
• Dynamic Obstacle Handling: Supports both static and dynamic obstacles, enabling robust performance in ever-changing environments.
• Real-Time Performance: Offers fast computation times suitable for real-time applications, ensuring timely decision-making and responsiveness.
• Versatile Kinematic Support: Compatible with various types of robot kinematics, including differential drive, Ackermann steering, and omnidirectional systems, providing flexibility for different robotic platforms.

Reference

Han, R., Wang, S., Wang, S., Zhang, Z., Zhang, Q., Eldar, Y. C., … & Pan, J. (2023). RDA: An accelerated collision free motion planner for autonomous navigation in cluttered environments. IEEE Robotics and Automation Letters, 8(3), 1715-1722.