A Risk Informed Task Planning Framework for Humanoid Robots in Hazardous Environments

This paper presents a generalized method to evaluate risks associated with humanoid robots executing manipulation tasks. Risks are defined as the product of probability, the likelihood of an event occurring, and severity, the resulting magnitude of harm should it occur. Rather than try to reduce the probability of failure events to zero, the objective of this work is to allow an experienced operator/supervisor to define if some failures are worse than others. In doing so, this allows the operator to judge whether high risk motions are necessary for the task at hand. Utilizing NASA's humanoid robot Valkyrie, our framework is demonstrated in both simulation and on the physical robot, with a pick and place task. We show that our method is capable of predicting failures for given motions based on their calculated risk.