Uncertainty Models for TTC-Based Collision-Avoidance


Authors: Zahra Forootaninia, Ioannis Karamouzas, Rahul Narain

We address the problem of uncertainty-aware local collision avoidance within the context of time-to-collision based navigation of multiple agents. We consider two specific models that account for uncertainty in the future trajectories of interacting agents: an isotropic model where the sensor error expands in all possible interaction directions between two given agents, and an adversarial model where the error is chosen assuming that the two agents are walking towards a head-on collision. We compare the two models experimentally via a number of simulation scenarios, and also provide theoretical guarantees about the collision avoidance behavior of the agents.