人間と共有する環境を移動するロボットの安全な動作計画
Safe Motion Planning for a Mobile Robot Navigating in Environments Shared with Humans
人間の動作予測に基づく危険度指標で経路長を重み付けしたコスト関数をRRT^Xに導入し、安全な動作計画を実現する手法を提案した。
著者: Basak Sakcak, Luca Bascetta
分類: cs.RO
原文アブストラクト
In this paper, a robot navigating an environment shared with humans is considered, and a cost function that can be exploited in $\text{RRT}^\text{X}$, a randomized sampling-based replanning algorithm that guarantees asymptotic optimality, to allow for a safe motion is proposed. The cost function is a path length weighted by a danger index based on a prediction of human motion performed using either a linear stochastic model, assuming constant longitudinal velocity and varying lateral velocity, and a GMM/GMR-based model, computed on an experimental dataset of human trajectories. The proposed approach is validated using a dataset of human trajectories collected in a real world setting.
