Human-Humanoid Interaction and Cooperation: a Review

Abstract

Purpose of Review Humanoid robots are versatile platforms with the potential to assist humans in several domains, from education to healthcare, from entertainment to the factory of the future. To find their place into our daily life, where complex interactions and collaborations with humans are expected, their social and physical interaction skills need to be further improved. Recent FindingsThe hallmark of humanoids is their anthropomorphic shape, which facilitates the interaction but at the same time increases the expectations of the human in terms of advanced cooperation capabilities. Cooperation with humans requires an appropriate modeling and real-time estimation of the human state and intention. This information is required both at a high level by the cooperative decision-making policy and at a low level by the interaction controller that implements the physical interaction. Real-time constraints induce simplified models that limit the decision capabilities of the robot during cooperation. SummaryIn this article, we review the current achievements in the context of human-humanoid interaction and cooperation. We report on the cognitive and cooperation skills that the robot needs to help humans achieve their goals, and how these high-level skills translate into the robot's low-level control commands. Finally, we report on the applications of humanoid robots as humans' companions, co-workers, or avatars. Keywords Humanoid robots • Human-robot interaction • CooperationThis article is part of the Topical Collection on Humanoid and Bipedal Robotics

Perspective Taking Reflects Beliefs About Partner Sophistication: Modern Computer Partners Versus Basic Computer and Human Partners

“…Such a shift in behavior likely reflects a larger change in attitudes and expectations toward computers as competent communicative partners, prompted by advancements in AI and the growing presence of interactive AI systems in everyday life (Horstmann & Krämer, 2019). In particular, in the last decade or so, we have seen a proliferation of research on human–robot interaction and collaboration (see Ajoudani et al., 2018; Vianello et al., 2021 for reviews). These studies highlight methodological and technological developments in human–robot interaction, the application of AI in various everyday contexts, and notably, robot as well as human adaptability in collaborative contexts (e.g., Nikolaidis, Hsu, & Srinivasa, 2017).…”

Research on LFD System of Humanoid Dual-Arm Robot

“…In order to interpret complex manipulation behaviors into a more mathematically tractable form [15][16][17][18][19][20][21][22][23][24], Calinon et al [25] used GMM to establish a probabilistic representation of demonstration data and used Gaussian mixture regression (GMR) to generate smooth trajectory curves. Evrard et al [26] proposed a probabilistic framework based on GMM and GMR for encoding and reconstructing robotic collaborative behavior.…”

Simultaneous Pose and Posture Estimation with a Two-stage Particle Filter for Visuo-inertial Fusion

“…This choice is a trade-off between a high fidelity biomechanical model and the size of the state space. We refer to the review by Vianello et al [17] on the importance of biomechanical models in context of Human-Robot collaboration. The mismatch between the observation DHM and our state DHM requires a form of retargeting, which will be taken care of by the estimation algorithm.…”