Characterizing the risk of operations is a fundamental requirement in robotics, and a crucial ingredient of safe planning. The problem is multifaceted, with multiple definitions arising in the vast recent literature fitting different application scenarios and leading to different computational approaches. A basic element shared by most frameworks is the definition and evaluation of the probability of collision for a mobile object in an environment with obstacles. We observe that, even in basic cases, different interpretations are possible. This paper proposes an index we call 'Risk Density', which offers a theoretical link between conceptually distant assumptions about the interplay of single collision events along a continuous path. We show how this index can be used to approximate the collision probability in the case where the robot evolves along a nominal continuous curve from random initial conditions. Indeed, under this hypothesis the proposed approximation outperforms some well-established methods either in accuracy or computational cost.
On the Evaluation of Collision Probability Along a Path
Paiola L.
Primo
;Grioli G.Secondo
;Bicchi A.Ultimo
2024-01-01
Abstract
Characterizing the risk of operations is a fundamental requirement in robotics, and a crucial ingredient of safe planning. The problem is multifaceted, with multiple definitions arising in the vast recent literature fitting different application scenarios and leading to different computational approaches. A basic element shared by most frameworks is the definition and evaluation of the probability of collision for a mobile object in an environment with obstacles. We observe that, even in basic cases, different interpretations are possible. This paper proposes an index we call 'Risk Density', which offers a theoretical link between conceptually distant assumptions about the interplay of single collision events along a continuous path. We show how this index can be used to approximate the collision probability in the case where the robot evolves along a nominal continuous curve from random initial conditions. Indeed, under this hypothesis the proposed approximation outperforms some well-established methods either in accuracy or computational cost.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.