Detecting Biological Motion for Human–Robot Interaction: A Link between Perception and Action

Abstract

One of the fundamental skills supporting safe and comfortable interaction between humans is their capability to understand intuitively each other's actions and intentions. At the basis of this ability is a special-purpose visual processing that human brain has developed to comprehend human motion. Among the first "building blocks" enabling the bootstrapping of such visual processing is the ability to detect movements performed by biological agents in the scene, a skill mastered by human babies in the first days of their life. In this paper, we present a computational model based on the assumption that such visual ability must be based on local low-level visual motion features, which are independent of shape, such as the configuration of the body and perspective. Moreover, we implement it on the humanoid robot iCub, embedding it into a software architecture that leverages the regularities of biological motion also to control robot attention and oculomotor behaviors. In essence, we put forth a model in which the regularities of biological motion link perception and action enabling a robotic agent to follow a human-inspired sensory-motor behavior. We posit that this choice facilitates mutual understanding and goal prediction during collaboration, increasing the pleasantness and safety of the interaction.

The ANEMONE: Theoretical Foundations for UX Evaluation of Action and Intention Recognition in Human-Robot Interaction

“…During the last two decades, research in the cognitive sciences fields, in particular embodied social cognition and cognitive neuroscience, has witnessed profound advancement in elucidating the underlying mechanisms of the recognition of actions and intentions in social interactions between humans that is fundamental to mutual interaction between humans, in which the mirror neuron system plays a significant role (e.g., [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ]). As pointed out by Vernon, Thill, and Ziemke [ 26 ], among others, there is a huge challenge to accomplish analogous mutual as well as fluent action and intention recognition between humans and robots as in social human-human interaction [ 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ], due to the apparent differences between the fundamental biological mechanisms in living human beings compared to the technological ones currently used in robots [ 17 , 19 , 25 , 26 , 27 , 28 , 29 ]. From a more embodied social cognition perspective, there is a major difference in how living agents enact a social world based on the underlying sensori-motor processes, particularly the mechanisms of the mirror neuron system, compared to the electrical wirings and technological implementation of artificial cognitive agents like robots [ 25 , 26 , 27 , …”

“…In the fields of HRI and robotics, there has been a lot of research on robots identifying, understanding, and predicting human intention and actions (e.g., [ 1 , 17 , 18 , 19 , 20 , 24 , 33 , 39 , 40 , 41 , 45 , 50 , 51 , 52 ]). It should be noted, however, that there is little existent work where robots are able to fully satisfy the requirements for having recognition capacities, although they display some aspect of recognition.…”

Social Cognition for Human-Robot Symbiosis—Challenges and Building Blocks

“…In other words, there is ground to believe that optimizing robotic movements to implicitly satisfy specific kinematic regularities (Casile et al, 2010 ) improves legibility of robot motions. This approach should generalize to different situations, different spatial configurations, or even different tasks (Busch et al, 2017 ), also taking into consideration how the regularities in kinematic patterns are mapped into the perceptual space of the observer (Vignolo et al, 2017 ), a sensory requirement for the legibility and exploitation of movement-based reciprocal communication.…”

Humane Robots—from Robots with a Humanoid Body to Robots with an Anthropomorphic Mind

“…Conversely, humans base most of their collaborative behavior on unsaid, covert information. The reading of implicit signals embedded in human actions enables the partners to read the mind and the emotions of the other and plays a crucial role in our social decisions (Sciutti et al 2018;Vignolo et al 2017). Intuition is the short term for this ability to capture the essence of what the other person really intends or wants.…”