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

The Event-Camera Dataset and Simulator: Event-based Data for Pose Estimation, Visual Odometry, and SLAM

New vision sensors, such as the Dynamic and Active-pixel Vision sensor (DAVIS), incorporate a conventional global-shutter camera and an event-based sensor in the same pixel array. These sensors have great potential for high-speed robotics and computer vision because they allow us to combine the benefits of conventional cameras with those of event-based sensors: low latency, high temporal resolution, and very high dynamic range. However, new algorithms are required to exploit the sensor characteristics and cope with its unconventional output, which consists of a stream of asynchronous brightness changes (called "events") and synchronous grayscale frames. For this purpose, we present and release a collection of datasets captured with a DAVIS in a variety of synthetic and real environments, which we hope will motivate research on new algorithms for high-speed and high-dynamic-range robotics and computer-vision applications. In addition to global-shutter intensity images and asynchronous events, we provide inertial measurements and ground-truth camera poses from a motion-capture system. The latter allows comparing the pose accuracy of ego-motion estimation algorithms quantitatively. All the data are released both as standard text files and binary files (i.e., rosbag). This paper provides an overview of the available data and describes a simulator that we release open-source to create synthetic event-camera data.Comment: 7 pages, 4 figures, 3 table

Gaze-based teleprosthetic enables intuitive continuous control of complex robot arm use: Writing & drawing

Eye tracking is a powerful mean for assistive technologies for people with movement disorders, paralysis and amputees. We present a highly intuitive eye tracking-controlled robot arm operating in 3-dimensional space based on the user's gaze target point that enables tele-writing and drawing. The usability and intuitive usage was assessed by a “tele” writing experiment with 8 subjects that learned to operate the system within minutes of first time use. These subjects were naive to the system and the task and had to write three letters on a white board with a white board pen attached to the robot arm's endpoint. The instructions are to imagine they were writing text with the pen and look where the pen would be going, they had to write the letters as fast and as accurate as possible, given a letter size template. Subjects were able to perform the task with facility and accuracy, and movements of the arm did not interfere with subjects ability to control their visual attention so as to enable smooth writing. On the basis of five consecutive trials there was a significant decrease in the total time used and the total number of commands sent to move the robot arm from the first to the second trial but no further improvement thereafter, suggesting that within writing 6 letters subjects had mastered the ability to control the system. Our work demonstrates that eye tracking is a powerful means to control robot arms in closed-loop and real-time, outperforming other invasive and non-invasive approaches to Brain-Machine-Interfaces in terms of calibration time (<;2 minutes), training time (<;10 minutes), interface technology costs. We suggests that gaze-based decoding of action intention may well become one of the most efficient ways to interface with robotic actuators - i.e. Brain-Robot-Interfaces - and become useful beyond paralysed and amputee users also for the general teleoperation of robotic and exoskeleton in human augmentation

Generic Techniques for the Calibration of Robots with Application of the 3-D Fixtures and Statistical Technique on the PUMA 500 and ARID Robots

A relatively simple, inexpensive, and generic technique that could be used in both laboratories and some operation site environments is introduced at the Robotics Applications and Development Laboratory (RADL) at Kennedy Space Center (KSC). In addition, this report gives a detailed explanation of the set up procedure, data collection, and analysis using this new technique that was developed at the State University of New York at Farmingdale. The technique was used to evaluate the repeatability, accuracy, and overshoot of the Unimate Industrial Robot, PUMA 500. The data were statistically analyzed to provide an insight into the performance of the systems and components of the robot. Also, the same technique was used to check the forward kinematics against the inverse kinematics of RADL's PUMA robot. Recommendations were made for RADL to use this technique for laboratory calibration of the currently existing robots such as the ASEA, high speed controller, Automated Radiator Inspection Device (ARID) etc. Also, recommendations were made to develop and establish other calibration techniques that will be more suitable for site calibration environment and robot certification