Human‐in‐the‐loop Control of a Humanoid Robot for Disaster Response: A Report from the DARPA Robotics Challenge Trials

Abstract

The DARPA Robotics Challenge (DRC) requires teams to integrate mobility, manipulation, and perception to accomplish several disaster-response tasks. We describe our hardware choices and software architecture, which enable human-in-the-loop control of a 28 degree-of-freedom ATLAS humanoid robot over a limited bandwidth link. We discuss our methods, results, and lessons learned for the DRC Trials tasks. The effectiveness of our system architecture was demonstrated as the WPI-CMU DRC Team scored 11 out of a possible 32 points, ranked seventh (out of 16) at the DRC Trials, and was selected as a finalist for the DRC Finals. C 2014 Wiley Periodicals, Inc.

Manipulation and Path Planning for KUKA (LWR/ LBR 4+) Robot in a Simulated and Real Environment

“…As described in this paper earlier, to perform object detection and localiza-tion using visual feedback, we want to integrate the developed libraries of bilateral KUKA LWR platform with libraries of Microsoft Kinnect camera, Barrett hand and shadow hand. Further, we will plan variety of motions for bilateral KUKA LWR platform like palletizing application in industrial environment [11] [16]. Finally but not limited to, we will use Python programming language to develop graphical user interface for each joint of bilateral KUKA LWR platform [17].…”

“…This developed package extends the capabilities of RViz interactive markers by allowing an operator to specify grasp poses in object-centric coordinate frames and multiple end-effector waypoint locations and to adjust these waypoints in order to meet the run-time demand of the task [10]. Mathew et al have explained their software architecture and hardware choices, which ensure human loop control of a 28 degree-of-freedom ATLAS humanoid robot over a limited bandwidth link [11]. Philipp et al have described a Robot Operating System based middleware software framework for the NimbRo-OP.…”

Team IHMC's Lessons Learned from the DARPA Robotics Challenge: Finding Data in the Rubble

“…The resulting graph structure is a visual description of the flexibility in the system. The coactive design method and the IA table provide a unique understanding of the system that is a significant change from talking about modes (Stentz et al., ), levels of operation (DeDonato et al., ), and task allocation (Fallon et al., ; Hebert et al., ). The graph makes it clear that discrete task allocation is not what is happening because the human is informed by automation and display elements, and automation can be assisted by the human as indicated by the numerous horizontal and diagonal lines shown in Figure .…”

Technical Overview of Team DRC‐Hubo@UNLV's Approach to the 2015 DARPA Robotics Challenge Finals

“…The Team NimbRo Rescue (a new entry team of DRC) also developed a quadruped platform, "Momaro," which has both legged and wheeled mechanisms (Behnke et al, 2015) for the Finals. On the other hand, teams that adopted "Atlas" adhered to the bipedal platform though massive update of its kinematic and dynamics implemented by Boston Dynamics (DeDonato et al, 2015;Fallon et al, 2015;Johnson et al, 2015;Knoedler, Dimitrov, Conn, Gennert, & Padir, 2015). Team Thor and Team AIST-Nedo also kept the original bipedal platform, "Thor" and "HRP-2Kai," with the minor changes (Cisneros et al, 2015;McGill, Yi, & Lee, 2015;Yi et al, 2014).…”