Collaborative autonomy between high-level behaviors and human operators for control of complex tasks with different humanoid robots

Abstract

This chapter discusses the common reactive high-level behavioral control system used by Team ViGIR and Team Hector on separate robots in the 2015 DARPA Robotics Challenge (DRC) Finals. We present an approach that allows one or more human operators to share control authority with a high-level behavior controller in the form of a finite state machine (automaton). This collaborative autonomy leverages the relative strengths of the robotic system and the (remote) human operators; it increases reliability of the human-robot team performance and decreases the task completion time. This approach is well-suited to disaster scenarios due to the unstructured nature of the environment. The system allows the operators to adjust the robotic system’s autonomy on-the-fly in response to changing circumstances, and to modify pre-defined behaviors as needed. To enable these high-level behaviors, we introduce our system designs for several of the lower-level system capabilities such as footstep planning and template-based object manipulation. We evaluate the proposed approach in the context of our two teams’ participation in the DRC Finals using two different humanoid platforms, and in systematic experiments conducted in the lab afterward. We present a discussion about the lessons learned during the DRC, especially those related to transitioning between operator-centered control and behavior-centered control during competition. Finally, we describe ongoing research beyond the DRC that extends the systems developed during the DRC. All of our described software is available as open source software.