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We describe the research and the integration methods we developed to make the HRP-2 humanoid robot climb vertical industrial-norm ladders. We use our multi-contact planner and multi-objective closed-loop control formulated as a QP (quadratic program). First, a set of contacts to climb the ladder is planned off-line (automatically or by the user). These contacts are provided as an input for a finite state machine. The latter builds supplementary tasks that account for geometric uncertainties and specific grasps procedures to be added to the QP controller. The latter provides instant desired states in terms of joint accelerations and contact forces to be tracked by the embedded low-level motor controllers. Our trials revealed that hardware changes are necessary, and parts of software must be made more robust. Yet, we confirmed that HRP-2 has the kinematic and power capabilities to climb real industrial ladders, such as those found in nuclear power plants and large scale manufacturing factories (e.g. aircraft, shipyard) and construction sites.

The center of mass (CoM) of a humanoid robot occupies a special place in its dynamics. As the location of its effective total mass, and consequently, the point of resultant action of gravity, the CoM is also the point where the robot’s aggregate linear momentum and angular momentum are naturally defined. The overarching purpose of this paper is to refocus our attention to centroidal dynamics : the dynamics of a humanoid robot projected at its CoM. In this paper we specifically study the properties, structure and computation schemes for the centroidal momentum matrix (CMM), which projects the generalized velocities of a humanoid robot to its spatial centroidal momentum. Through a transformation diagram we graphically show the relationship between this matrix and the well-known joint-space inertia matrix. We also introduce the new concept of “average spatial velocity” of the humanoid that encompasses both linear and angular components and results in a novel decomposition of the kinetic energy. Further, we develop a very efficient O ( N ) algorithm, expressed in a compact form using spatial notation, for computing the CMM, centroidal momentum, centroidal inertia, and average spatial velocity. Finally, as a practical use of centroidal dynamics we show that a momentum-based balance controller that directly employs the CMM can significantly reduce unnecessary trunk bending during balance maintenance against external disturbance.

This paper describes a collection of optimization algorithms for achieving dynamic planning, control, and state estimation for a bipedal robot designed to operate reliably in complex environments. To make challenging locomotion tasks tractable, we describe several novel applications of convex, mixed-integer, and sparse nonlinear optimization to problems ranging from footstep placement to whole-body planning and control. We also present a state estimator formulation that, when combined with our walking controller, permits highly precise execution of extended walking plans over non-flat terrain. We describe our complete system integration and experiments carried out on Atlas, a full-size hydraulic humanoid robot built by Boston Dynamics, Inc.

In the late 1990s using robotic technology to assist children with Autistic Spectrum Condition (ASD) emerged as a potentially useful area of research. Since then the field of assistive robotics for children with ASD has grown considerably with many academics trialling different robots and approaches. One such robot is the humanoid robot Kaspar that was originally developed in 2005 and has continually been built upon since, taking advantage of technological developments along the way. A key principle in the development of Kaspar since its creation has been to ensure that all of the advances to the platform are driven by the requirements of the users. In this paper we discuss the development of Kaspar’s design and explain the rationale behind each change to the platform. Designing and building a humanoid robot to interact with and help children with ASD is a multidisciplinary challenge that requires knowledge of the mechanical engineering, electrical engineering, Human–Computer Interaction (HCI), Child–Robot Interaction (CRI) and knowledge of ASD. The Kaspar robot has benefited from the wealth of knowledge accrued over years of experience in robot-assisted therapy for children with ASD. By showing the journey of how the Kaspar robot has developed we aim to assist others in the field develop such technologies further.

We have been developing a paradigm that we call learning-from-observation for a robot to automatically acquire a robot program to conduct a series of operations, or for a robot to understand what to do, through observing humans performing the same operations. Since a simple mimicking method to repeat exact joint angles or exact end-effector trajectories does not work well because of the kinematic and dynamic differences between a human and a robot, the proposed method employs intermediate symbolic representations, tasks, for conceptually representing what-to-do through observation. These tasks are subsequently mapped to appropriate robot operations depending on the robot hardware. In the present work, task models for upper-body operations of humanoid robots are presented, which are designed on the basis of Labanotation. Given a series of human operations, we first analyze the upper-body motions and extract certain fixed poses from key frames. These key poses are translated into tasks represented by Labanotation symbols. Then, a robot performs the operations corresponding to those task models. Because tasks based on Labanotation are independent of robot hardware, different robots can share the same observation module, and only different task-mapping modules specific to robot hardware are required. The system was implemented and demonstrated that three different robots can automatically mimic human upper-body operations with a satisfactory level of resemblance.

Previous research has shown that features of synthetic robot faces suggesting social categories produce predictable and consequential social judgments. Artificial robot faces that are feminine (versus masculine) and humanlike (versus machinelike) have been shown to be judged as warmer and to produce relatively higher levels of comfort, resulting in positive evaluations and a greater desire for engagement. Two studies pursued these questions using images of real robots. In Study 1, images of existing robots were used to manipulate gendered features and machineness. Study 2 used an assortment of images of real robots including non-humanoid exemplars that vary naturally in gendered features and machineness. Consistent results emerged from the two studies. In both studies, robots were evaluated more positively and produced a greater desire for contact to the degree that they were seen as humanlike and feminine. These results attest to the importance of social factors in predicting responses to robots. Implications for robot design and future research are discussed.

The discussion around gendering humanoid robots has gained more traction in the last few years. To lay the basis for a full comprehension of how robots’ “gender” has been understood within the Human–Robot Interaction (HRI) community—i.e., how it has been manipulated, in which contexts, and which effects it has yielded on people’s perceptions and interactions with robots—we performed a scoping review of the literature. We identified 553 papers relevant for our review retrieved from 5 different databases. The final sample of reviewed papers included 35 papers written between 2005 and 2021, which involved a total of 3902 participants. In this article, we thoroughly summarize these papers by reporting information about their objectives and assumptions on gender (i.e., definitions and reasons to manipulate gender), their manipulation of robots’ “gender” (i.e., gender cues and manipulation checks), their experimental designs (e.g., demographics of participants, employed robots), and their results (i.e., main and interaction effects). The review reveals that robots’ “gender” does not affect crucial constructs for the HRI, such as likability and acceptance, but rather bears its strongest effect on stereotyping. We leverage our different epistemological backgrounds in Social Robotics and Gender Studies to provide a comprehensive interdisciplinary perspective on the results of the review and suggest ways to move forward in the field of HRI.

Sex robots are likely to play an important role in shaping public understandings of sex and of relations between the sexes in the future. This paper contributes to the larger project of understanding how they will do so by examining the ethics of the “rape” of robots. I argue that the design of realistic female robots that could explicitly refuse consent to sex in order to facilitate rape fantasy would be unethical because sex with robots in these circumstances is a representation of the rape of a woman, which may increase the rate of rape, expresses disrespect for women, and demonstrates a significant character defect. Even when the intention is not to facilitate rape, the design of robots that can explicitly refuse consent is problematic due to the likelihood that some users will experiment with raping them. Designing robots that lack the capacity to explicitly refuse consent may be morally problematic depending on which of two accounts of the representational content of sex with realistic humanoid robots is correct.

Social touch interactions can, depending on the type and strength of the dyadic social relationship, elicit a plethora of physiological, emotional, and behavioral responses; both beneficial and disadvantageous. With the intention to expand the communicative capabilities of humanoid social robots, we investigated whether robot-initiated touches could elicit beneficial responses in the human user that are comparable to responses to human touch. In addition, we investigated whether having a pre-existing positive social bond with the robot modulates these responses. To this end, we conducted a 2 × 2 between subjects experiment ( N = 67) in which participants either did or did not establish a bond with the robot prior to interacting with it during stressful circumstances. This interaction either did or did not comprise robot-initiated touches. We hypothesized that robotic touches would attenuate the subjective and physiological stress responses during the stressful event (H1a), enhance the perceived relation with the robot (H1b), and increase one’s pro-social behavior (H1c), as contrasted with interactions without touch. Based on findings from human touch, we also expected that the effects of H1a and H1b would be more outspoken when a bond with the robot was established (H2). Our findings imply that robotic touches attenuated physiological stress responses and increased the perceived intimacy of the human–robot bond. No effects were found on pro-social behavior and all effects were independent of whether a bond was formed or not. Although no full support for our hypotheses was found, the findings suggest that robot-initiated touch can, under specific circumstances, be a valuable extension of a social robot’s nonverbal communication repertoire.

Humanoid robot represents a highly uncertain dynamic plant. Nowadays, humanoid push recovery in stepping represents a complicated and challenging task. This paper proposes a new control approach in order to improve the biped push recovery using flywheel-based auto-balance. The core of the proposed approach relies on the original implementation of an additional control scheme that equalizes the unexpected force acting on the humanoid during robust stepping. Our novel control approach includes an evolutionary neural ( IDE-NN: Improved Differential Evolution-Neural Networks ) controller for robust biped walking and an additional optimal Proportional Integral (PI) used to regulate the flywheel integrated to the humanoid upper body. The proposed solution helps the humanoid stepping robustly to follow the trajectory required and further empirically guarantees the small-sized experiment humanoid HUBOT-5 robot stably stepping, even in case an unexpected force acting on HUBOT-5 biped. The comprehensive benchmark tests confirm that our proposed method is initiatively efficient.