论文标题
避免障碍的移动：一种数据驱动的风险感知方法
Moving Obstacle Avoidance: a Data-Driven Risk-Aware Approach
论文作者
论文摘要
本文提出了一种新的结构化方法，以预测动态移动障碍的路径并使用风险感知模型预测控制（MPC）方案。给定对先验未知障碍轨迹的嘈杂测量值，自举技术可以预测一组障碍轨迹。自举预测纳入了MPC优化中，使用风险感知方法，以提供避免障碍物的概率保证。我们使用三维多旋转无人机的模拟来验证我们的方法，该无人机避免了各种移动的障碍物，例如扔球和带有空气阻力的飞盘。
This paper proposes a new structured method for a moving agent to predict the paths of dynamically moving obstacles and avoid them using a risk-aware model predictive control (MPC) scheme. Given noisy measurements of the a priori unknown obstacle trajectory, a bootstrapping technique predicts a set of obstacle trajectories. The bootstrapped predictions are incorporated in the MPC optimization using a risk-aware methodology so as to provide probabilistic guarantees on obstacle avoidance. We validate our methods using simulations of a 3-dimensional multi-rotor drone that avoids various moving obstacles, such as a thrown ball and a frisbee with air drag.
