Analysis of human–robot interaction at the DARPA Robotics Challenge Finals

Abstract

In June 2015, the Defense Advanced Research Projects Agency (DARPA) Robotics Challenge (DRC) Finals were held in Pomona, California. The DRC Finals served as the third phase of the program designed to test the capabilities of semi-autonomous, remote humanoid robots to perform disaster response tasks with degraded communications. All competition teams were responsible for developing their own interaction method to control their robot. Of the 23 teams in the competition, 20 consented to participate in this study of human–robot interaction (HRI). The evaluation team observed the consenting teams during task execution in their control rooms (with the operators), and all 23 teams were observed on the field during the public event (with the robot). A variety of data were collected both before the competition and on-site. Each participating team’s interaction methods were distilled into a set of characteristics pertaining to the robot, operator strategies, control methods, and sensor fusion. Each task was decomposed into subtasks that were classified according to the complexity of the mobility and/or manipulation actions being performed. Performance metrics were calculated regarding the number of task attempts, performance time, and critical incidents, which were then correlated to each team’s interaction methods. The results of this analysis suggest that a combination of HRI characteristics, including balancing the capabilities of the operator with those of the robot and multiple sensor fusion instances with variable reference frames, positively impacted task performance. A set of guidelines for designing HRI with remote, semi-autonomous humanoid robots is proposed based on these results.

Leveraging depth data in remote robot teleoperation interfaces for general object manipulation

“…Remote robot interaction interfaces are highly sensitive to bandwidth limitations and network latency. This is true in high-quality network environments, such as that utilized in our work, and becomes even more critical in applications such as search and rescue, as shown in the DARPA Robotics Challenge (DRC; see Yanco et al (2015) and Norton et al (2017) for discussions of interaction under degraded communications in the DRC trials and finals, respectively), and space robotics, as characterized by Sheridan (1993). In this work, we compared two categories of interfaces characterized by different visualization modes.…”

Type Design and Behavior Control for Six Legged Robots

“…Particularly, after the Fukushima nuclear accident in Japan, the U.S. Defense Department held the DRAPA Robotics Competition for emergency rescue by conducting the following tasks: driving car, get off the car, open and close the door, screw the valve, break the wall, plug the power, clear obstacles, climb up and down the stairs [64]. It is noteworthy that all the participating teams are using HRI control [65].…”

“…Teams competing in the DARPA Finals exhibited one or more of the following HRI characteristics [65]: 1The robot had more autonomy when performing simpler manipulation and mobility tasks; (2) The operators had more interaction performing complex manipulation and mobility tasks; (3) More models are placed manually to assist robots in performing complicated manipulation tasks; (4) Operators were well trained with ample practice and more than one operator split responsibilities in task executions.…”

“…After the competition, a comprehensive analysis review published in International Journal of Robotics Research (IJRR) summarized the experience and lessons learned in the DRAPA competition [65]. The paper concludes that the state of autonomous control in robotics was far from sufficient to support effective teleoperation when completing complex tasks.…”

Mechanism, Actuation, Perception, and Control of Highly Dynamic Multilegged Robots: A Review

“…The payloads of these hexapod robots can reach up to 500 kg. In the DARPA Robotics Challenge held in 2015, many humanoid robots successfully performed various rescue operations, such as driving a car, cutting a pipe, and opening a door in a simulated disaster scenario of a nuclear power plant [9]. These new-generation legged robots featured high-level force and vision perception systems, enabling force control and obstacle avoidance.…”