skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Accomplishing Robotic Autonomy: The Complexities of Sociotechnical Care and Agency in the Laboratory
Effective ethical interventions in emerging technologies such as robotic autonomy demand situated understandings of the practices that shape them. Drawing upon a year of participatory ethnography, this study examines the sociomaterial practices used to accomplish robotic agency in an engineering research laboratory. Ironically, the robot was often a helpless, even pathetic, figure. Roboticists displayed an attitude of surprisingly genuine, diligent, and self-effacing care toward the robot as they helped enable it to perform basic competencies such as picking up a bottle. Using a practice theory, we show how roboticists’ care practices, motivated and sustained by anticipatory narratives of robotic agency, accomplish robotic autonomy. We argue that interventions must acknowledge and engage with the complex dynamics of technologists’ care to be effective.  more » « less
Award ID(s):
2219236
PAR ID:
10636104
Author(s) / Creator(s):
;
Publisher / Repository:
Communication and Social Robotics Labs
Date Published:
Journal Name:
Human-Machine Communication
Volume:
9
ISSN:
2638-602X
Page Range / eLocation ID:
143 to 166
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. null (Ed.)
    ABSTRACT Introduction Short response time is critical for future military medical operations in austere settings or remote areas. Such effective patient care at the point of injury can greatly benefit from the integration of semi-autonomous robotic systems. To achieve autonomy, robots would require massive libraries of maneuvers collected with the goal of training machine learning algorithms. Although this is attainable in controlled settings, obtaining surgical data in austere settings can be difficult. Hence, in this article, we present the Dexterous Surgical Skill (DESK) database for knowledge transfer between robots. The peg transfer task was selected as it is one of the six main tasks of laparoscopic training. In addition, we provide a machine learning framework to evaluate novel transfer learning methodologies on this database. Methods A set of surgical gestures was collected for a peg transfer task, composed of seven atomic maneuvers referred to as surgemes. The collected Dexterous Surgical Skill dataset comprises a set of surgical robotic skills using the four robotic platforms: Taurus II, simulated Taurus II, YuMi, and the da Vinci Research Kit. Then, we explored two different learning scenarios: no-transfer and domain-transfer. In the no-transfer scenario, the training and testing data were obtained from the same domain; whereas in the domain-transfer scenario, the training data are a blend of simulated and real robot data, which are tested on a real robot. Results Using simulation data to train the learning algorithms enhances the performance on the real robot where limited or no real data are available. The transfer model showed an accuracy of 81% for the YuMi robot when the ratio of real-tosimulated data were 22% to 78%. For the Taurus II and the da Vinci, the model showed an accuracy of 97.5% and 93%, respectively, training only with simulation data. Conclusions The results indicate that simulation can be used to augment training data to enhance the performance of learned models in real scenarios. This shows potential for the future use of surgical data from the operating room in deployable surgical robots in remote areas. 
    more » « less
  2. Users play an integral role in the performance of many robotic systems, and robotic systems must account for differences in users to improve collaborative performance. Much of the work in adapting to users has focused on designing teleoperation controllers that adjust to extrinsic user indicators such as force, or intent, but do not adjust to intrinsic user qualities. In contrast, the Human-Robot Interaction community has extensively studied intrinsic user qualities, but results may not rapidly be fed back into autonomy design. Here we provide foundational evidence for a new strategy that augments current shared control, and provide a mechanism to directly feed back results from the HRI community into autonomy design. Our evidence is based on a study examining the impact of the user quality “locus of control” on telepresence robot performance. Our results support our hypothesis that key user qualities can be inferred from human-robot interactions (such as through path deviation or time to completion) and that switching or adaptive autonomies might improve shared control performance. 
    more » « less
  3. Desjardin, S. and (Ed.)
    Building Information Modeling (BIM) is a critical data source for constructing new structures depicting the inner workings of the systems and components in detail. However, current modeling practices are based on traditional construction methods, resulting in insufficient details within the BIM model to support robotic construction for many building systems. The model’s level of development (LOD) needs to be increased to facilitate the changes in data requirements. One method that allows for increased LOD is computational modeling; however, many factors can influence the process. Therefore, this study investigates challenges for implementation to increase the LOD for building to enable robotic construction. Dynamo is used as the computational modeling software in conjunction with Autodesk Revit to accomplish this. A process was created to place various components, such as concrete masonry units (CMUs), in their final design location and extract information utilizing these platforms for masonry construction. However, challenges were met during this process, including material naming conventions, tolerance/specification inputs, wall openings/lintels, and component/material libraries. The challenges presented during the implementation of the Dynamo mirror what the literature shows for supporting technological infrastructure BIM and mobile robot construction. To accomplish this research, an extensive literature review was completed, along with documentation of challenges during the development and implementation of the script. 
    more » « less
  4. This paper presents a mixed-methods study of app-based motorcycle taxis in Thailand to explore the social dynamics of rideshare drivers and their exercised autonomy both through social pressure and a hostile work environment. As motorcycle taxis are open-air vehicles, drivers can be exposed to prolonged air pollution and other weather events, potentially impacting their health. In an initial quantitative study of server-side rideshare logs, we unexpectedly found that drivers do not exercise the autonomy provided by their rideshare platform to avoid air pollution events. This prompted a follow-on investigation through semi-structured interviews of both drivers and passengers in three provinces to explore why these drivers fail to experience the autonomy promised by gig-work in this context and elucidated further examples this lack of autonomy experienced by drivers. Our study sheds light on the social context that may constrain a driver's agency, including financial pressures, weather conditions, conflicts with local taxi organizations, and a false perception that drivers need to work around the ride assignment algorithm to avoid being blacklisted. We find that when leveraging app-based rideshare opportunities, drivers simultaneously perceive increased flexibility in their work hours and a lack of agency to prioritize their health and safety. We conclude with a discussion on potential interventions aimed at mitigating the forces preventing drivers from exercising their autonomy. 
    more » « less
  5. We present the Human And Robot Multimodal Observations of Natural Interactive Collaboration (HARMONIC) dataset. This is a large multimodal dataset of human interactions with a robotic arm in a shared autonomy setting designed to imitate assistive eating. The dataset provides human, robot, and environmental data views of 24 different people engaged in an assistive eating task with a 6-degree-of-freedom (6-DOF) robot arm. From each participant, we recorded video of both eyes, egocentric video from a head-mounted camera, joystick commands, electromyography from the forearm used to operate the joystick, third-person stereo video, and the joint positions of the 6-DOF robot arm. Also included are several features that come as a direct result of these recordings, such as eye gaze projected onto the egocentric video, body pose, hand pose, and facial keypoints. These data streams were collected specifically because they have been shown to be closely related to human mental states and intention. This dataset could be of interest to researchers studying intention prediction, human mental state modeling, and shared autonomy. Data streams are provided in a variety of formats such as video and human-readable CSV and YAML files. 
    more » « less