Ishaan Khare1 Jyotish Poonganam1 Bharath Gopalakrishnan1 K. Madhava Krishna1
In this paper, we explore Probabilistic Inverse Velocity Obstacle (PIVO) as an alternative to probabilistic versions of Velocity Obstacles (PVO) for free flying quadrotor systems. Inverse Velocity Obstacles compute effective controls from a sequence of observations on other agents without the need to access ego state information. As a direct consequence of this the ego state noise is not entailed in probabilistic formulations bringing in verifiable advantages in the form of reduced path lengths, less conservative maneuvers, reduced occurrences of stopping/hovering to let others pass. These advantages are vividly tabulated in this paper, showcasing the efficacy of PIVO as an alternative to probabilistic versions of Velocity Obstacles. In particular we show the benefits of PIVO over PVO in relation to sample complexity as well as overall trajectory lengths. We also show the efficacy of our probabilistic formulation in handling non-parametric and often multimodal noise distributions.