RRT and Velocity Obstacles-based motion planning for Unmanned Aircraft Systems Traffic Management (UTM)

RFPPO：基于运动动态RRT的流场-PPO用于动态地形跟随/地形回避航路规划

RFPPO: Motion Dynamic RRT based Fluid Field - PPO for Dynamic TF/TA Routing Planning

本文提出RFPPO方法，将运动动态RRT与流场、人工势场及PPO相结合，重新设计状态动作空间和奖励函数，在真实DEM数据上实现了无需全局规划且满足动态约束的长距离TF/TA航路规划。

Multi-agent RRT*: Sampling-based Cooperative Pathfinding (Extended Abstract)

Cooperative pathfinding is a problem of finding a set of non-conflicting trajectories for a number of mobile agents. Its applications include planning for teams of mobile robots, such as autonomous aircrafts, cars, or underwater vehicles. The state-of-the-art algorithms for cooperative pathfinding typically rely on some heuristic forward-search pathfinding technique, where A* is often the algorithm of choice. Here, we propose MA-RRT*, a novel algorithm for multi-agent path planning that builds upon a recently proposed asymptotically-optimal sampling-based algorithm for finding single-agent sho…

SkyTrakx: A Toolkit for Simulation and Verification of Unmanned Air-Traffic Management Systems (Extended Version)

The key concept for safe and efficient traffic management for Unmanned Aircraft Systems (UAS) is the notion of operation volume (OV). An OV is a 4-dimensional block of airspace and time, which can express an aircraft's intent, and can be used for planning, de-confliction, and traffic management. While there are several high-level simulators for UAS Traffic Management (UTM), we are lacking a framework for creating, manipulating, and reasoning about OVs for heterogeneous air vehicles. In this paper, we address this and present SkyTrakx -- a software toolkit for simulation and verification of UTM…

Rapid Uncertainty Propagation and Chance-Constrained Path Planning for Small Unmanned Aerial Vehicles

With the number of small Unmanned Aircraft Systems (sUAS) in the national airspace projected to increase in the next few years, there is growing interest in a traffic management system capable of handling the demands of this aviation sector. It is expected that such a system will involve trajectory prediction, uncertainty propagation, and path planning algorithms. In this work, we use linear covariance propagation in combination with a quadratic programming-based collision detection algorithm to rapidly validate declared flight plans. Additionally, these algorithms are combined with a Dynamic,…

Obstacle Avoidance for UAS in Continuous Action Space Using Deep Reinforcement Learning

Obstacle avoidance for small unmanned aircraft is vital for the safety of future urban air mobility (UAM) and Unmanned Aircraft System (UAS) Traffic Management (UTM). There are many techniques for real-time robust drone guidance, but many of them solve in discretized airspace and control, which would require an additional path smoothing step to provide flexible commands for UAS. To provide a safe and efficient computational guidance of operations for unmanned aircraft, we explore the use of a deep reinforcement learning algorithm based on Proximal Policy Optimization (PPO) to guide autonomous …