Although different types of teams increasingly employ embodied physical action (EPA) robots as a collaborative technology to accomplish their work, we know very little about what makes such teams successful. This paper has two objectives: the first is to examine whether a team’s emotional attachment to its robots can lead to better team performance and viability; the second is to determine whether robot and team identification can promote a team’s emotional attachment to its robots. To achieve these objectives, we conducted a between-subjects experiment with 57 teams working with robots. Teams performed better and were more viable when they were emotionally attached to their robots. Both robot and team identification increased a team’s emotional attachment to its robots. Results of this study have implications for collaboration using EPA robots specifically and for collaboration technology in general.

Emotional Attachment, Performance, and Viability in Teams Collaborating with Embodied Physical Action (EPA) Robots

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.

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Analysis of Human-robot Interaction at the DARPA Robotics Challenge Trials

Motivated by the DARPA Robotics Challenge (DRC), the application of operator assisted (semi-)autonomous robots with highly complex locomotion and manipulation abilities is considered for solving complex tasks in potentially unknown and unstructured environments. Because of the limited a priori knowledge about the state of the environment and tasks needed to achieve a complex mission, a sufficiently complete a priori design of high level robot behaviors is not possible. Most of the situational knowledge required for such behavior design is gathered only during runtime and needs to be interpreted by a human operator. However, current behavior control approaches only allow for very limited adaptation at runtime and no flexible operator interaction. In this paper an approach for definition and execution of complex robot behaviors based on hierarchical state machines is presented, allowing to flexibly change the structure of behaviors on the fly during runtime through assistance of a remote operator. The efficiency of the proposed approach is demonstrated and evaluated not only in an example scenario, but also by application in two robot competitions.

Human-robot collaborative high-level control with application to rescue robotics

Teleoperation offers the possibility of imparting robotic systems with sophisticated reasoning skills, intuition, and creativity to perform tasks. However, current teleoperation solutions for high degree-of-actuation (DoA), multi-fingered robots are generally cost-prohibitive, while low-cost offerings usually provide reduced degrees of control. Herein, a low-cost, vision based teleoperation system, DexPilot, was developed that allows for complete control over the full 23 DoA robotic system by merely observing the bare human hand. DexPilot enables operators to carry out a variety of complex manipulation tasks that go beyond simple pick-and-place operations. This allows for collection of high dimensional, multi-modality, state-action data that can be leveraged in the future to learn sensorimotor policies for challenging manipulation tasks. The system performance was measured through speed and reliability metrics across two human demonstrators on a variety of tasks. The videos of the experiments can be found at this https URL.

DexPilot: Vision Based Teleoperation of Dexterous Robotic Hand-Arm System

The deployment of robots to assist in environments hostile for humans during emergency scenarios require robots to demonstrate enhanced physical performance, that includes adequate power, adaptability and robustness to physical interactions and efficient operation. This work presents the design and development of the lower body of the new high performance humanoid WALK-MAN, a robot developed recently to assist in disaster response scenarios. The paper introduces the details of the WALK-MAN lower-body, highlighting the innovative design optimization features considered to maximize the leg performance. Starting from the general lower body specifications the objectives of the design and how they were addressed are introduced, including the selection of the leg kinematics, the arrangement of the actuators and their integration with the leg structure to maximize the range of motion, reduce the leg mass and inertia, and shape the leg mass distribution for better dynamic performance. Physical robustness is ensured with the integration of elastic transmission and impact energy absorbing covers. Experimental walking trials demonstrate the correct operation of the legs while executing a walking gait.

WALK-MAN humanoid lower body design optimization for enhanced physical performance

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...

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

This paper provides an overview of the development of a unique unmanned underwater harbor surveillance technology and reviews possible mission spaces. One of Boston Engineering's biomimetic UUV technologies, the BIOSwimmer, leverages a biologically inspired design to rapidly provide Homeland Security with actionable intelligence. The Department of Homeland Security is tasked with uncovering attempts to disrupt, damage, or illegally use the flow of commerce; without hindering it. This is a difficult process as a balance needs to be attained to sufficiently monitor ports, rivers and waterways without slowing commerce. The BIOSwimmer is designed to be deployed rapidly, maneuver into locations previously inaccessible to current platforms and effectively provide enhanced intelligence far beyond current capability. These advantages make it possible to effectively protect ports and inland waterways with a human-robot team, expanding the capabilities of security personnel.

BIOSwimmer: Enabling technology for port security

The DARPA Robotics Challenge (DRC) was a competition designed to advance the capabilities of remotely teleoperated semi-autonomous humanoid robots performing in a disaster response scenario with degraded communications. Throughout the DRC, our evaluation team conducted two studies of human-robot interaction (HRI) for the Trials and Finals competitions. From these studies, we have generated recommendations and design guidelines for HRI with remote, semi-autonomous humanoids, but our findings also have implications outside of the competition’s domain. In this article, we discuss our perspectives on effective and ineffective human-robot teams based upon our experiences at the DRC. We consider the impact of various interfacing and control techniques, the effect of versatile robot design on task performance, and the operational context under which these factors work together to function in a human-centric environment. We use these underlying components of HRI to review how the advancements made at the DRC can be applied to present day robot applications and key capabilities for effective human-robot teams in the future.

Willard Ober

Papers

Analysis of Human-robot Interaction at the DARPA Robotics Challenge Trials

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

BIOSwimmer: Enabling technology for port security

Perspectives on Human-Robot Team Performance from an Evaluation of the DARPA Robotics Challenge