Zhenrui Yue, Huimin Zeng, Yimeng Lu, Lanyu Shang, Yang Zhang, Dong Wang. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). 2024.

This paper considers safe robot mission planning in uncertain dynamical environments. This problem arises in applications such as surveillance, emergency rescue, and autonomous driving. It is a challenging problem due to mod-eling and integrating dynamical uncertainties into a safe planning framework, and finding a solution in a computationally tractable way. In this work, we first develop a probabilistic model for dynamical uncertainties. Then, we provide a framework to generate a path that maximizes safety for complex missions by incorporating the uncertainty model. We also devise a Monte Carlo method to obtain a safe path efficiently. Finally, we evaluate the performance of our approach and compare it to potential alternatives in several case studies.

We present a complete design and implementation of a system that consists of multiple quadrotors playing capture the flag game. Our main contributions in this work include a custom built quadrotor platform, an efficient implementation of a distributed trajectory planning algorithm, and a WiFi based communication infrastructure. In our design, we equip the quadrotors with autopilot modules for low level control. Moreover, we install low power computing modules for implementing the distributed trajectory planning algorithm online. Furthermore, we develop a communication infrastructure to enable coordination among the quadrotors, which is required for computing a suboptimal control action in real time. The interactions among all the hardware and software components are managed at a higher level by Robot Operating System (ROS). To test the performance of the system, we select a motivating setup of capture the flag game, which is an adversarial game played between two teams of agents called attack and defense. The system is initially simulated in the Gazebo robot simulator with software in the loop. Finally, the complete system is tested and the flight testing results are presented.