Enabling Depth-driven Visual Attention on the iCub Humanoid Robot: Instructions for Use and New Perspectives

The importance of depth perception in the interactions that humans have within their nearby space is a well established fact. Consequently, it is also well known that the possibility of exploiting good stereo information would ease and, in many cases, enable, a large variety of attentional and interactive behaviors on humanoid robotic platforms. However, the difficulty of computing real-time and robust binocular disparity maps from moving stereo cameras often prevents from relying on this kind of cue to visually guide robots' attention and actions in real-world scenarios. The contribution of this paper is two-fold: first, we show that the Efficient Large-scale Stereo Matching algorithm (ELAS) by A. Geiger et al. 2010 for computation of the disparity map is well suited to be used on a humanoid robotic platform as the iCub robot; second, we show how, provided with a fast and reliable stereo system, implementing relatively challenging visual behaviors in natural settings can require much less effort. As a case of study we consider the common situation where the robot is asked to focus the attention on one object close in the scene, showing how a simple but effective disparity-based segmentation solves the problem in this case. Indeed this example paves the way to a variety of other similar applications

On the Calibration of Active Binocular and RGBD Vision Systems for Dual-Arm Robots

This paper describes a camera and hand-eye calibration methodology for integrating an active binocular robot head within a dual-arm robot. For this purpose, we derive the forward kinematic model of our active robot head and describe our methodology for calibrating and integrating our robot head. This rigid calibration provides a closedform hand-to-eye solution. We then present an approach for updating dynamically camera external parameters for optimal 3D reconstruction that are the foundation for robotic tasks such as grasping and manipulating rigid and deformable objects. We show from experimental results that our robot head achieves an overall sub millimetre accuracy of less than 0.3 millimetres while recovering the 3D structure of a scene. In addition, we report a comparative study between current RGBD cameras and our active stereo head within two dual-arm robotic testbeds that demonstrates the accuracy and portability of our proposed methodology

A Portable Bio-Inspired Architecture for Efficient Robotic Vergence Control

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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

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

Stereo vision-based self-localization system for RoboCup

[[abstract]]This work proposes a new Stereo Vision-Based Self-Localization System (SVBSLS) for the RoboCup soccer humanoid league rules for the 2010 competition. The humanoid robot integrates the information from the pan/tilt motors and stereo vision to accomplish the self-localization and measure the distance of the robot and the soccer ball. The proposed approach uses the trigonometric function to find the coarse distances from the robot to the landmark and the robot to the soccer ball, and then it further adopts the artificial neural network technique to increase the precision of the distance. The statistics approach is also used to calculate the relationship between the humanoid robot and the position of the landmark for self-localization. The experimental results indicate that the localization system of SVBSLS in this research work has 100% average accuracy ratio for localization. The average error of distance from the humanoid soccer robot to the soccer ball is only 0.64 cm.[[notice]]需補會議日期、性質、主辦單位[[conferencedate]]20110627~2011063

Stereo Matching in the Presence of Sub-Pixel Calibration Errors

Stereo matching commonly requires rectified images that are computed from calibrated cameras. Since all under-lying parametric camera models are only approximations, calibration and rectification will never be perfect. Additionally, it is very hard to keep the calibration perfectly stable in application scenarios with large temperature changes and vibrations. We show that even small calibration errors of a quarter of a pixel are severely amplified on certain structures. We discuss a robotics and a driver assistance example where sub-pixel calibration errors cause severe problems. We propose a filter solution based on signal theory that removes critical structures and makes stereo algorithms less sensitive to calibration errors. Our approach does not aim to correct decalibration, but rather to avoid amplifications and mismatches. Experiments on ten stereo pairs with ground truth and simulated decalibrations as well as images from robotics and driver assistance scenarios demonstrate the success and limitations of our solution that can be combined with any stereo method