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 Active Binocular Robot Vision Architecture for Scene Exploration

We present a portable active binocular robot vision archi- tecture that integrates a number of visual behaviours. This vision archi- tecture inherits the abilities of vergence, localisation, recognition and si- multaneous identification of multiple target object instances. To demon- strate the portability of our vision architecture, we carry out qualitative and comparative analysis under two different hardware robotic settings, feature extraction techniques and viewpoints. Our portable active binoc- ular robot vision architecture achieved average recognition rates of 93.5% for fronto-parallel viewpoints and, 83% percentage for anthropomorphic viewpoints, respectively

Robust visual servoing in 3d reaching tasks

This paper describes a novel approach to the problem of reaching an object in space under visual guidance. The approach is characterized by a great robustness to calibration errors, such that virtually no calibration is required. Servoing is based on binocular vision: a continuous measure of the end-effector motion field, derived from real-time computation of the binocular optical flow over the stereo images, is compared with the actual position of the target and the relative error in the end-effector trajectory is continuously corrected. The paper outlines the general framework of the approach, shows how visual measures are obtained and discusses the synthesis of the controller along with its stability analysis. Real-time experiments are presented to show the applicability of the approach in real 3-D applications

Single-Shot Clothing Category Recognition in Free-Configurations with Application to Autonomous Clothes Sorting

This paper proposes a single-shot approach for recognising clothing categories from 2.5D features. We propose two visual features, BSP (B-Spline Patch) and TSD (Topology Spatial Distances) for this task. The local BSP features are encoded by LLC (Locality-constrained Linear Coding) and fused with three different global features. Our visual feature is robust to deformable shapes and our approach is able to recognise the category of unknown clothing in unconstrained and random configurations. We integrated the category recognition pipeline with a stereo vision system, clothing instance detection, and dual-arm manipulators to achieve an autonomous sorting system. To verify the performance of our proposed method, we build a high-resolution RGBD clothing dataset of 50 clothing items of 5 categories sampled in random configurations (a total of 2,100 clothing samples). Experimental results show that our approach is able to reach 83.2\% accuracy while classifying clothing items which were previously unseen during training. This advances beyond the previous state-of-the-art by 36.2\%. Finally, we evaluate the proposed approach in an autonomous robot sorting system, in which the robot recognises a clothing item from an unconstrained pile, grasps it, and sorts it into a box according to its category. Our proposed sorting system achieves reasonable sorting success rates with single-shot perception.Comment: 9 pages, accepted by IROS201

Stereoscopic human interfaces

This article focuses on the use of stereoscopic video interfaces for telerobotics. Topics concerning human visual perception, binocular image capturing, and stereoscopic devices are described. There is a wide variety of video interfaces for telerobotic systems. Choosing the best video interface depends on the telerobotic application requirements. Simple monoscopic cameras are good enough for watching remote robot movements or for teleprogramming a sequence of commands. However, when operators seek precise robot guidance or wish to manipulate objects, a better perception of the remote environment must be achieved, for which more advanced visual interfaces are required. This implies a higher degree of telepresence, and, therefore, the most suitable visual interface has to be chosen. The aim of this article is to describe the two main aspects using stereoscopic interfaces: the capture of binocular video images, according to the disparity limits in human perception and the proper selection of the visualization interface for stereoscopic images

A Portable Bio-Inspired Architecture for Efficient Robotic Vergence Control

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Spatial context-aware person-following for a domestic robot

Domestic robots are in the focus of research in terms of service providers in households and even as robotic companion that share the living space with humans. A major capability of mobile domestic robots that is joint exploration of space. One challenge to deal with this task is how could we let the robots move in space in reasonable, socially acceptable ways so that it will support interaction and communication as a part of the joint exploration. As a step towards this challenge, we have developed a context-aware following behav- ior considering these social aspects and applied these together with a multi-modal person-tracking method to switch between three basic following approaches, namely direction-following, path-following and parallel-following. These are derived from the observation of human-human following schemes and are activated depending on the current spatial context (e.g. free space) and the relative position of the interacting human. A combination of the elementary behaviors is performed in real time with our mobile robot in different environments. First experimental results are provided to demonstrate the practicability of the proposed approach