Project Highlights

RDA: Open-Source Platform for Fast Collision Avoidance Model Predictive Control

Project link: https://github.com/hanruihua/rda_ros

RDA planner is a fast and efficient motion planner for autonomous navigation in cluttered environments. The key idea of RDA is to decompose the complex optimization problem into several subproblems by ADMM, which allows the collision avoidance constraints to be computed in parallel for each obstacle to reduce computation time significantly. Key features:

• Shape aware planner, which can tackle robots and obstacles with arbitrary convex shapes.
• Highly accurate control achieved through the use of an optimization solver.
• Support for both static and dynamic obstacles.
• Fast computation time, which is suitable for real-time applications.
• Support different types of dynamics, including differential, Ackermann, and omnidirectional robots.

CarlaFLCAV: Open-Source Platform for Design and Verification of Federated Learning Automonous Driving

Project link: https://github.com/SIAT-INVS/CarlaFLCAV

CarlaFLCAV is an open-source FLCAV simulation platform based on CARLA simulator that supports:

• Multi-modal dataset generation: Including point-cloud, image, radar data with associated calibration, synchronization, and annotation
• Training and inference: Examples for CAV perception, including object detection, traffic sign detection, and weather classification
• Various FL frameworks: FedAvg, device selection, noisy aggregation, parameter selection, distillation, and personalization
• Optimization based modules: Network resource and road sensor pose optimization.