Immersive Teleoperation of the Eye Gaze of Social Robots Assessing Gaze-Contingent Control of Vergence, Yaw and Pitch of Robotic Eyes

International audienceThis paper presents a new teleoperation system – called stereo gaze-contingent steering (SGCS) – able to seamlessly control the vergence, yaw and pitch of the eyes of a humanoid robot – here an iCub robot – from the actual gaze direction of a remote pilot. The video stream captured by the cameras embedded in the mobile eyes of the iCub are fed into an HTC Vive R Head-Mounted Display equipped with an SMI R binocular eye-tracker. The SGCS achieves the effective coupling between the eye-tracked gaze of the pilot and the robot's eye movements. SGCS both ensures a faithful reproduction of the pilot's eye movements – that is perquisite for the readability of the robot's gaze patterns by its interlocutor – and maintains the pilot's oculomotor visual clues – that avoids fatigue and sickness due to sensorimotor conflicts. We here assess the precision of this servo-control by asking several pilots to gaze towards known objects positioned in the remote environment. We demonstrate that we succeed in controlling vergence with similar precision as eyes' azimuth and elevation. This system opens the way for robot-mediated human interactions in the personal space, notably when objects in the shared working space are involved

Peripersonal Space in the Humanoid Robot iCub

Developing behaviours for interaction with objects close to the body is a primary goal for any organism to survive in the world. Being able to develop such behaviours will be an essential feature in autonomous humanoid robots in order to improve their integration into human environments. Adaptable spatial abilities will make robots safer and improve their social skills, human-robot and robot-robot collaboration abilities. This work investigated how a humanoid robot can explore and create action-based representations of its peripersonal space, the region immediately surrounding the body where reaching is possible without location displacement. It presents three empirical studies based on peripersonal space findings from psychology, neuroscience and robotics. The experiments used a visual perception system based on active-vision and biologically inspired neural networks. The first study investigated the contribution of binocular vision in a reaching task. Results indicated the signal from vergence is a useful embodied depth estimation cue in the peripersonal space in humanoid robots. The second study explored the influence of morphology and postural experience on confidence levels in reaching assessment. Results showed that a decrease of confidence when assessing targets located farther from the body, possibly in accordance to errors in depth estimation from vergence for longer distances. Additionally, it was found that a proprioceptive arm-length signal extends the robot’s peripersonal space. The last experiment modelled development of the reaching skill by implementing motor synergies that progressively unlock degrees of freedom in the arm. The model was advantageous when compared to one that included no developmental stages. The contribution to knowledge of this work is extending the research on biologically-inspired methods for building robots, presenting new ways to further investigate the robotic properties involved in the dynamical adaptation to body and sensing characteristics, vision-based action, morphology and confidence levels in reaching assessment.CONACyT, Mexico (National Council of Science and Technology

A hierarchical system for a distributed representation of the peripersonal space of a humanoid robot

Reaching a target object in an unknown and unstructured environment is easily performed by human beings. However, designing a humanoid robot that executes the same task requires the implementation of complex abilities, such as identifying the target in the visual field, estimating its spatial location, and precisely driving the motors of the arm to reach it. While research usually tackles the development of such abilities singularly, in this work we integrate a number of computational models into a unified framework, and demonstrate in a humanoid torso the feasibility of an integrated working representation of its peripersonal space. To achieve this goal, we propose a cognitive architecture that connects several models inspired by neural circuits of the visual, frontal and posterior parietal cortices of the brain. The outcome of the integration process is a system that allows the robot to create its internal model and its representation of the surrounding space by interacting with the environment directly, through a mutual adaptation of perception and action. The robot is eventually capable of executing a set of tasks, such as recognizing, gazing and reaching target objects, which can work separately or cooperate for supporting more structured and effective behaviors

Motor Eyes: Mechanical Platform for a Binocular Robotic Vision System

Stereoscopic vision systems require high computational power to perform image processing for 3D reconstruction of a scene. Synchronizing eye movements through mechanical coupling can reduce this processing power. To investigate this potential, the project team developed a mechanical platform for a binocular robotic vision system that uses stepper motors and slider linkages to achieve coupled pan, coupled tilt and coupled vergence eye movements. A prototype, controlled by an Arduino Uno, was constructed. The prototype achieved eye rotation speeds comparable to human saccadic eye motion and was capable of focusing on specified points with some position error caused by the prototype’s high sensitivity to misalignments of mechanical parts

Motor Eyes: Mechanical Platform for a Binocular Robotic Vision System

Stereoscopic vision systems require high computational power to perform image processing for 3D reconstruction of a scene. Synchronizing eye movements through mechanical coupling can reduce this processing power. To investigate this potential, the project team developed a mechanical platform for a binocular robotic vision system that uses stepper motors and slider linkages to achieve coupled pan, coupled tilt and coupled vergence eye movements. A prototype, controlled by an Arduino Uno, was constructed. The prototype achieved eye rotation speeds comparable to human saccadic eye motion and was capable of focusing on specified points with some position error caused by the prototype’s high sensitivity to misalignments of mechanical parts

A hierarchical system for a distributed representation of the peripersonal space of a humanoid robot

Reaching a target object in an unknown and unstructured environment is easily performed by human beings. However, designing a humanoid robot that executes the same task requires the implementation of complex abilities, such as identifying the target in the visual field, estimating its spatial location, and precisely driving the motors of the arm to reach it. While research usually tackles the development of such abilities singularly, in this work we integrate a number of computational models into a unified framework, and demonstrate in a humanoid torso the feasibility of an integrated working representation of its peripersonal space. To achieve this goal, we propose a cognitive architecture that connects several models inspired by neural circuits of the visual, frontal and posterior parietal cortices of the brain. The outcome of the integration process is a system that allows the robot to create its internal model and its representation of the surrounding space by interacting with the environment directly, through a mutual adaptation of perception and action. The robot is eventually capable of executing a set of tasks, such as recognizing, gazing and reaching target objects, which can work separately or cooperate for supporting more structured and effective behaviors

Motor Eyes: Mechanical Platform for a Binocular Robotic Vision System

Stereoscopic vision systems require high computational power to perform image processing for 3D reconstruction of a scene. Synchronizing eye movements through mechanical coupling can reduce this processing power. To investigate this potential, the project team developed a mechanical platform for a binocular robotic vision system that uses stepper motors and slider linkages to achieve coupled pan, coupled tilt and coupled vergence eye movements. A prototype, controlled by an Arduino Uno, was constructed. The prototype achieved eye rotation speeds comparable to human saccadic eye motion and was capable of focusing on specified points with some position error caused by the prototype’s high sensitivity to misalignments of mechanical parts

Immersive Teleoperation of the Eye Gaze of Social Robots Assessing Gaze-Contingent Control of Vergence, Yaw and Pitch of Robotic Eyes

International audienceThis paper presents a new teleoperation system – called stereo gaze-contingent steering (SGCS) – able to seamlessly control the vergence, yaw and pitch of the eyes of a humanoid robot – here an iCub robot – from the actual gaze direction of a remote pilot. The video stream captured by the cameras embedded in the mobile eyes of the iCub are fed into an HTC Vive R Head-Mounted Display equipped with an SMI R binocular eye-tracker. The SGCS achieves the effective coupling between the eye-tracked gaze of the pilot and the robot's eye movements. SGCS both ensures a faithful reproduction of the pilot's eye movements – that is perquisite for the readability of the robot's gaze patterns by its interlocutor – and maintains the pilot's oculomotor visual clues – that avoids fatigue and sickness due to sensorimotor conflicts. We here assess the precision of this servo-control by asking several pilots to gaze towards known objects positioned in the remote environment. We demonstrate that we succeed in controlling vergence with similar precision as eyes' azimuth and elevation. This system opens the way for robot-mediated human interactions in the personal space, notably when objects in the shared working space are involved