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1. A Humanoid Robot Object Perception Approach Using Depth Images

   https://doi.org/10.1109/NAECON46414.2019.9057808  

   Cofield, Aaron ; El-Shair, Zaid ; Rawashdeh, Samir A. ( January 2019 , Proceedings of IEEE National Aerospace and Electronics Conference (NAECON))

   null (Ed.)

   Humanoid robots have had significant research interest in the past two decades. Their classification as mobile manipulators allows them to work in unstructured environments creating new possibilities for human-robot interaction. Object grasping and manipulation are essential and enabling capabilities for mobile humanoid robots that require reliable perception. This paper presents a perception approach using depth images from an RGB-D camera to estimate the work plane and estimate object positions relative to the robot. Results from experiments with a set of object shapes and scenarios are presented. 

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2. Teleoperation of Humanoid Robots: A Survey

   https://doi.org/10.1109/TRO.2023.3236952  

   Darvish, Kourosh ; Penco, Luigi ; Ramos, Joao ; Cisneros, Rafael ; Pratt, Jerry ; Yoshida, Eiichi ; Ivaldi, Serena ; Pucci, Daniele ( February 2023 , IEEE Transactions on Robotics)

   Teleoperation of humanoid robots enables the integration of the cognitive skills and domain expertise of humans with the physical capabilities of humanoid robots. The operational versatility of humanoid robots makes them the ideal platform for a wide range of applications when teleoperating in a remote environment. However, the complexity of humanoid robots imposes challenges for teleoperation, particularly in unstructured dynamic environments with limited communication. Many advancements have been achieved in the last decades in this area, but a comprehensive overview is still missing. This survey article gives an extensive overview of humanoid robot teleoperation, presenting the general architecture of a teleoperation system and analyzing the different components. We also discuss different aspects of the topic, including technological and methodological advances, as well as potential applications. 

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3. Toward next-generation learned robot manipulation

   https://doi.org/10.1126/scirobotics.abd9461  

   Cui, Jinda ; Trinkle, Jeff ( May 2021 , Science Robotics)

   The ever-changing nature of human environments presents great challenges to robot manipulation. Objects that robots must manipulate vary in shape, weight, and configuration. Important properties of the robot, such as surface friction and motor torque constants, also vary over time. Before robot manipulators can work gracefully in homes and businesses, they must be adaptive to such variations. This survey summarizes types of variations that robots may encounter in human environments and categorizes, compares, and contrasts the ways in which learning has been applied to manipulation problems through the lens of adaptability. Promising avenues for future research are proposed at the end.

    

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4. Deploying the NASA Valkyrie Humanoid for IED Response: An Initial Approach and Evaluation Summary

   Steven Jorgensen, Michael Lanighan ( January 2019 , IEEE-RAS International Conference on Humanoid Robots)

   As part of a feasibility study, this paper shows the NASA Valkyrie humanoid robot performing an end- to-end improvised explosive device (IED) response task. To demonstrate and evaluate robot capabilities, sub-tasks highlight different locomotion, manipulation, and perception requirements: traversing uneven terrain, passing through a narrow passageway, opening a car door, retrieving a suspected IED, and securing the IED in a total containment vessel (TCV). For each sub-task, a description of the technical approach and the hidden challenges that were overcome during development are presented. The discussion of results, which explicitly includes existing limitations, is aimed at motivating continued research and development to enable practical deployment of humanoid robots for IED response. 

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5. Why Should We Gender?: The Effect of Robot Gendering and Occupational Stereotypes on Human Trust and Perceived Competency

   https://doi.org/10.1145/3319502.3374778  

   Bryant, De'Aira ; Borenstein, Jason ; Howard, Ayanna ( March 2020 , HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction)

   The attribution of human-like characteristics onto humanoid robots has become a common practice in Human-Robot Interaction by designers and users alike. Robot gendering, the attribution of gender onto a robotic platform via voice, name, physique, or other features is a prevalent technique used to increase aspects of user acceptance of robots. One important factor relating to acceptance is user trust. As robots continue to integrate themselves into common societal roles, it will be critical to evaluate user trust in the robot's ability to perform its job. This paper examines the relationship among occupational gender-roles, user trust and gendered design features of humanoid robots. Results from the study indicate that there was no significant difference in the perception of trust in the robot's competency when considering the gender of the robot. This expands the findings found in prior efforts that suggest performance-based factors have larger influences on user trust than the robot's gender characteristics. In fact, our study suggests that perceived occupational competency is a better predictor for human trust than robot gender or participant gender. As such, gendering in robot design should be considered critically in the context of the application by designers. Such precautions would reduce the potential for robotic technologies to perpetuate societal gender stereotypes. 

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