Gaussian 不确定性下移动规划的精确性和边界碰撞概率 (Exact and Bounded Collision Probability for Motion Planning under Gaussian Uncertainty)

Computing collision-free trajectories is of prime importance for safe navigation. We present an approach for computing the collision probability under Gaussian distributed motion and sensing uncertainty with the robot and static obstacle shapes approximated as ellipsoids. The collision condition is formulated as the distance between ellipsoids and unlike previous approaches we provide a method for computing the exact collision probability. Furthermore, we provide a tight upper bound that can be computed much faster during online planning. Comparison to other state-of-the-art methods is also provided. The proposed method is evaluated in simulation under varying configuration and number of obstacles.

翻译：无计算机碰撞轨迹对于安全航行至关重要。我们提出了一个计算高森分布式运动下的碰撞概率和对机器人和静态障碍形状的不确定性的感测和感测方法,这些形状近似于椭球状的机器人和静态障碍形状。碰撞状态的表述是椭球体之间的距离,不同于以前我们提供的计算精确碰撞概率的方法。此外, 我们提供了一个紧凑的上限, 在网上规划期间可以更快速地计算。还提供了与其他最新方法的比较。在模拟中,以不同的配置和障碍数量对拟议方法进行了评估。