Alberto Romay

Human-robot Teaming for Rescue Missions: Team ViGIR's Approach to the 2013 DARPA Robotics Challenge Trials

Team ViGIR entered the 2013 DARPA Robotics Challenge DRC with a focus on developing software to enable an operator to guide a humanoid robot through the series of challenge tasks emulating disaster response scenarios. The overarching philosophy was to make our operators full team members and not just mere supervisors. We designed our operator control station OCS to allow multiple operators to request and share information as needed to maintain situational awareness under bandwidth constraints, while directing the robot to perform tasks with most planning and control taking place onboard the robot. Given the limited development time, we leveraged a number of open source libraries in both our onboard software and our OCS design; this included significant use of the robot operating system libraries and toolchain. This paper describes the high level approach, including the OCS design and major onboard components, and it presents our DRC Trials results. The paper concludes with a number of lessons learned that are being applied to the final phase of the competition and are useful for related projects as well.

Template-based manipulation in unstructured environments for supervised semi-autonomous humanoid robots

Humanoid robotic manipulation in unstructured environments is a challenging problem. Limited perception, communications and environmental constraints present challenges that prevent fully autonomous or purely teleoperated robots from reliably interacting with their environment. In order to achieve higher reliability in manipulation we present an approach involving remote human supervision. Strengths from both human operator and humanoid robot are leveraged through a user interface that allows the operator to perceive the remote environment through an aggregated worldmodel based on onboard sensing, while the robot can efficiently receive perceptual and semantic information from the operator. A template based manipulation approach has been successfully applied to the Atlas humanoid robot; we show real world footage of the results obtained in the DARPA Robotics Challenge Trials 2013.

Achieving versatile manipulation tasks with unknown objects by supervised humanoid robots based on object templates

The investigations of this paper are motivated by the scenario of a supervised semi-autonomous humanoid robot entering a mainly unknown, potentially degraded human environment to perform highly diverse disaster recovery tasks. For this purpose, the robot must be enabled to use any object it can find in the environment as tool for achieving its current manipulation task. This requires the use of potential unknown objects as well as known objects for new purposes (e.g. using a drill as a hammer). A recently proposed object template manipulation approach is extended to provide a semi-autonomous humanoid robot assisted by a remote human supervisor with the versatility needed to utilize objects in the described manner applying affordances [1] from other previously known objects. For an Atlas humanoid robot it is demonstrated how using a small set of such object templates with well defined affordances can be used to solve manipulation tasks using new unknown objects.

Overview of team ViGIR's approach to the Virtual Robotics Challenge

With the DARPA Robotics Challenge (DRC), a call to an ambitious multi-part competition was sent out to the robotics community. In this paper, we briefly summarize the approach for addressing the Virtual Robotics Challenge (VRC) where software for control and supervision of a capable humanoid robot must be developed. Team ViGIR, comprising members from the US and Germany, leveraged previous robotics competition experience and a variety of open source tools, to achieve sixth place in the VRC out of 126 registrants, thereby advancing to the next round of the DRC and obtaining an Atlas robot.

An Object Template Approach to Manipulation for Humanoid Avatar Robots for Rescue Tasks

Nowadays, the first steps towards the use of remote mobile robots to perform rescue tasks in disaster environments have been made possible. However, these environments still present several challenges for robots, which open new possibilities for research and development. For example, fully autonomous robots are not yet suitable for such tasks with high degree of uncertainty, and pure teloperated robots require high expertise and high mental workload, as well as fast communication to be reliable. In this paper, we discuss a middle ground approach to manipulation, that leverages the strengths and abilities of a human supervisor and a semi-autonomous robot while at the same tackling their weaknesses. This approach is based on the object template concept, which provides an interaction method to rapidly communicate to a remote robot the physical and abstract information for manipulation of the objects of interest. This approach goes beyond current grasp-centered approaches by focusing on the affordance information of the objects and providing flexibility to solve manipulation tasks in versatile ways. Experimental evaluation of the approach is performed using two highly advanced humanoid robots.

Open source driving controller concept for humanoid robots: Teams hector and ViGIR at 2015 DARPA robotics challenge finals

Among the eight tasks of the DARPA Robotics Challenge (DRC), the driving task was one of the most challenging. Obstacles in the course prevented straight driving and restricted communications limited the situation awareness of the operator. In this video we show how Team Hector and Team ViGIR successfully completed the driving task with different robot platforms, THOR-Mang and Atlas respectively, but using the same software and compliant steering adapter. Our driving user interface presents to the operator image view from cameras and driving aids such as wheel positioning and turn radius path of the wheels. The operator uses a standard computer game joystick which is used to command steering wheel angles and gas pedal pressure. Steering wheel angle positions are generated off-line and interpolated on-line in the robots onboard computer. The compliant steering adapter accommodates end-effector positioning errors. Gas pedal pressure is generated by a binary joint position of the robots leg. Commands are generated in the operator control station and sent as target positions to the robot. The driving user interface also provides feedback from the current steering wheel position. Video footage with descriptions from the driving interface, robots camera and LIDAR perception and external task monitoring is presented.

Hose task at the 2013 DARPA Robotics Challenge trials: Team ViGIR's results video

Summary form only given. Team ViGIR entered the 2013 DARPA Robotics Challenge (DRC) with a focus on developing software to enable an operator to guide a humanoid robot through the series of challenge tasks emulating disaster scenarios. We designed our operator control station (OCS) to allow multiple operators to request and share information as needed to maintain situational awareness under bandwidth constraints, while directing the robot to perform tasks with most planning and control taking place onboard the robot. Given the limited development time we leveraged a number of open source libraries in both our onboard software and our OCS design; this included significant use of the Robot Operating System (ROS) libraries and toolchain. The DRC consisted of 8 tasks; this video shows our approach for the Hose task, where the remote operator guides the robot through the OCS to walk towards a reel to pick up a hose, then walk with the hose towards a wye and attach the hose to it. Synchronized footage from both, Hose scenario and screen cast of the OCS, shows step by step how the operator interacts with the robot through template based manipulation and high level semantic commands like defining waypoints or objects to be grasped.

Collaborative Autonomy Between High-Level Behaviors and Human Operators for Control of Complex Tasks with Different Humanoid Robots

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.