In December 2013, the Defense Advanced Research Projects Agency (DARPA) Robotics Challenge (DRC) Trials were held in Homestead, Florida. The DRC Trials were designed to test the capabilities of humanoid robots in disaster response scenarios with degraded communications. Each team created their own interaction method to control their robot, either the Boston Dynamics Atlas robot or a robot built by the team itself. Of the 15 competing teams, eight participated in our study of human-robot interaction. We observed the participating teams from the field (with the robot) and in the control room (with the operators), noting many performance metrics, such as critical incidents and utterances, and categorizing their interaction methods according to the number of operators, control methods, and amount of interaction. We decomposed each task into a series of subtasks, different from the DRC Trials official subtasks for points, to gain a better understanding of each team's performance in varying complexities of mobility and manipulation. Each team's interaction methods have been compared to their performance, and correlations have been analyzed to understand why some teams ranked higher than others. We discuss lessons learned from this study, and we have found in general that the guidelines for human-robot interaction for unmanned ground vehicles still hold true: more sensor fusion, fewer operators, and more automation lead to better performance. C 2015 Wiley Periodicals, Inc.Journal of Field Robotics DOI 10.1002/rob 422 • Journal of Field Robotics-2015 primary guidelines applicable to the design of HRI within the USAR domain:
Exposure to microgravity during spaceflight is known to elicit orientation illusions, errors in sensory localization, postural imbalance, changes in vestibulo-spinal and vestibulo-ocular reflexes, and space motion sickness. The objective of this experiment was to investigate whether an alteration in cognitive visual-spatial processing, such as the perception of distance and size of objects, is also taking place during prolonged exposure to microgravity. Our results show that astronauts on board the International Space Station exhibit biases in the perception of their environment. Objects’ heights and depths were perceived as taller and shallower, respectively, and distances were generally underestimated in orbit compared to Earth. These changes may occur because the perspective cues for depth are less salient in microgravity or the eye-height scaling of size is different when an observer is not standing on the ground. This finding has operational implications for human space exploration missions.
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.
The U.S. military medical community spends a great deal of time and resources training its personnel to provide them with the knowledge and skills necessary to perform life-saving tasks, both on the battlefield and at home. However, personnel may fail to retain specialized knowledge and skills if they are not applied during the typical periods of nonuse within the military deployment cycle, and retention of critical knowledge and skills is crucial to the successful care of warfighters. For example, we researched the skill and knowledge loss associated with specialized surgical skills such as those required to perform laparoscopic surgery (LS) procedures. These skills are subject to decay when military surgeons perform combat casualty care during their deployment instead of LS. This article describes our preliminary research identifying critical LS skills, as well as their acquisition and decay rates. It introduces models that identify critical skills related to laparoscopy, and proposes objective metrics for measuring these critical skills. This research will provide insight into best practices for (1) training skills that are durable and resistant to skill decay, (2) assessing these skills over time, and (3) introducing effective refresher training at appropriate intervals to maintain skill proficiency.
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