Supervision and teleoperation of high degree-of-freedom robots is a complex task due to environmental constraints such as obstacles and limited communication, as well as task specific requirements such as using more than one end-effector at the same time. In this work we present a supervision and teleoperation framework that allows an operator to see the surroundings of a robot in 3D, make necessary adjustments for a dual or single arm manipulation task, preview the task in simulation before execution, and finally execute the task on a real robot. The framework has been applied to the valve turning task of the DARPA Robotics Challenge on the PR2, Hubo2+, and DRCHubo robots.

In this paper, we report lessons learned through the design of a framework for teleoperating a humanoid robot to perform a manipulation task. We present a software framework for cooperative traded control that enables a team of operators to control a remote humanoid robot over an unreliable communications link. The framework produces statically-stable motion trajectories that are collision-free and respect end-effector pose constraints. After operator confirmation, these trajectories are sent over the data link for execution on the robot. Additionally, we have defined a clear operational procedure for the operators to manage the teleoperation task. We applied our system to the valve turning task in the DARPA Robotics Challenge (DRC). Our framework is able to perform reliably and is resilient to unreliable network conditions, as we demonstrate in a set of test runs performed remotely over the internet. We analyze our approach and discuss lessons learned which may be useful for others when designing such a system.