Safe and Efficient Exploration of Human Models During Human-Robot Interaction

Abstract

Generating safe behaviors for autonomous systems is important as they continue to be deployed in the real world, especially around people. In this work, we focus on developing a novel safe controller for systems where there are multiple sources of uncertainty. We formulate a novel multimodal safe control method, called the Multimodal Safe Set Algorithm (MMSSA) for the case where the agent has uncertainty over which discrete mode the system is in, and each mode itself contains additional uncertainty. To our knowledge, this is the first energy-function-based safe control method applied to systems with multimodal uncertainty. We apply our controller to a simulated human-robot interaction where the robot is uncertain of the human's true intention and each potential intention has its own additional uncertainty associated with it, since the human is not a perfectly rational actor. We compare our proposed safe controller to existing safe control methods and find that it does not impede the system performance (i.e. efficiency) while also improving the safety of the system.

Safe contact-based robot active search using Bayesian optimization and control barrier functions

“…However, here we are more interested in methods that consider the safety of the controlled system, that is, the robot, as a query deemed safe algorithmically can still result in an unsafe robot action due to uncertainty in the control and environmental dynamics. Various methods have been proposed, such as safe control based on energy functions ( Pandya and Liu, 2022 ), safe model predictive control ( Koller et al, 2018 ), and Bayesian meta-learning through alternating sequential optimal control problems for exploration and exploitation ( Lew et al, 2022 ). A prominent approach to safety is control barrier functions (CBFs), a framework for ensuring the safety of nonlinear control affine systems ( Ames et al, 2014 ; Romdlony and Jayawardhana, 2014 ; Ames et al, 2019 ).…”