23,442 research outputs found

    Position Determination of a Robot End-Effector Using a 6D-Measurement System Based on the Two-View Vision

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    A mechatronic system based on the micro-macro-kinematic consists of an industrial robot and a piezoelectric stage mounted on the robot’s end-effector and has to carry out operations like micro-assembly or micro-milling. The piezoelectric stage has to compensate the positioning error of the robot. Therefore, the position of the robot’s end-effector has to be measured with high accuracy. This paper presents a high accuracy 6D-measurement system, which is used to determine the position and orientation of the robot’s end-effector. We start with the description of the operational concept and components of the measurement system. Then we look at image processing methods, camera calibration and reconstruction methods and choose the most accurate ones. We apply the well-known pin-hole camera model to calibrate single cameras. Then we apply the epipolar geometry to describe the relationship between two cameras and calibrate them as a stereo vision system. A distortion model is also applied to enhance the accuracy of the system. The measurement results are presented in the end of the paper

    Sensor-based automated path guidance of a robot tool

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    The objective of the research is to develop a robot capability for a simultaneous measurement of the orientation (surface normal) and position of a 3-dimensional unknown object for a precise tool path guidance and control. The proposed system can guide the robot manipulator while maintaining specific orientation between the robot end-effector and the workpiece and also generate a measured geometric CAD database; The first phase involves the computer graphics simulation of an automated guidance and control of a robot tool using the proposed scheme. In the simulation, an object of known geometry is used for camera image data generation and subsequently determining the position and orientation of surface points based only on the simulated camera image information. Based on this surface geometry measurement technique, robot tool guidance and path planning algorithm is developed; The second phase involves the laboratory experiment. To demonstrate the validity of the proposed measurement method, the result of CCD image processing (grey to binary image conversion, thinning of binary image, detection of cross point, etc) and the calibration of the cameras/lighting source are performed. (Abstract shortened by UMI.)

    An Active helideck testbed for floating structures based on a Stewart-Gough platform

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    A parallel robot testbed based on Stewart-Gough platform called Active-helideck is designed, developed and tested as a helicopter floating helideck. The objective of this testbed is to show the advantages of helicopters that use an active helideck upon landing on and taking off from ships or from offshore structures. Active-helideck compensates simulated movements of a ship at sea. The main goal of this study is to maintain the robot’s end effector (helideck) in a quasi-static position in accordance to an absolute inertial frame. Compensation is carried out through the coordinate action of its six prismatic actuators in function of an inertial measurement unit. Moreover, the simulation of the sea movement is done by a parallel robot called ship platform with three degrees of freedom. The ship platform is built with a vertical oscillation along the z axis, i.e. heave, and rotates on remaining axes, i.e. roll and pitch. Active helideck is able to compensate simulated movements by considering the ship as an inertial frame as observed in the experiment

    Whole-Body MPC for a Dynamically Stable Mobile Manipulator

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    Autonomous mobile manipulation offers a dual advantage of mobility provided by a mobile platform and dexterity afforded by the manipulator. In this paper, we present a whole-body optimal control framework to jointly solve the problems of manipulation, balancing and interaction as one optimization problem for an inherently unstable robot. The optimization is performed using a Model Predictive Control (MPC) approach; the optimal control problem is transcribed at the end-effector space, treating the position and orientation tasks in the MPC planner, and skillfully planning for end-effector contact forces. The proposed formulation evaluates how the control decisions aimed at end-effector tracking and environment interaction will affect the balance of the system in the future. We showcase the advantages of the proposed MPC approach on the example of a ball-balancing robot with a robotic manipulator and validate our controller in hardware experiments for tasks such as end-effector pose tracking and door opening

    Multidimensional Capacitive Sensing for Robot-Assisted Dressing and Bathing

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    Robotic assistance presents an opportunity to benefit the lives of many people with physical disabilities, yet accurately sensing the human body and tracking human motion remain difficult for robots. We present a multidimensional capacitive sensing technique that estimates the local pose of a human limb in real time. A key benefit of this sensing method is that it can sense the limb through opaque materials, including fabrics and wet cloth. Our method uses a multielectrode capacitive sensor mounted to a robot's end effector. A neural network model estimates the position of the closest point on a person's limb and the orientation of the limb's central axis relative to the sensor's frame of reference. These pose estimates enable the robot to move its end effector with respect to the limb using feedback control. We demonstrate that a PR2 robot can use this approach with a custom six electrode capacitive sensor to assist with two activities of daily living-dressing and bathing. The robot pulled the sleeve of a hospital gown onto able-bodied participants' right arms, while tracking human motion. When assisting with bathing, the robot moved a soft wet washcloth to follow the contours of able-bodied participants' limbs, cleaning their surfaces. Overall, we found that multidimensional capacitive sensing presents a promising approach for robots to sense and track the human body during assistive tasks that require physical human-robot interaction.Comment: 8 pages, 16 figures, International Conference on Rehabilitation Robotics 201

    Simulation, modelling and development of the metris RCA

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    In partnership with Metris UK we discuss the utilisation of modelling and simulation methods in the development of a revolutionary 7-axis Robot CMM Arm (RCA). An offline virtual model is described, facilitating pre-emptive collision avoidance and assessment of optimal placement of the RCA relative to scan specimens. Workspace accessibility of the RCA is examined under a range of geometrical assumptions and we discuss the effects of arbitrary offsets resulting from manufacturing tolerances. Degeneracy is identified in the number of ways a given pose may be attained and it is demonstrated how a simplified model may be exploited to solve the inverse kinematics problem of finding the “correct” set of joint angles. We demonstrate how the seventh axis may be utilised to avoid obstacles or otherwise awkward poses, giving the unit greater dexterity than traditional CMMs. The results of finite element analysis and static force modelling on the RCA are presented which provide an estimate of the forces exerted on the internal measurement arm in a range of poses

    Markerless visual servoing on unknown objects for humanoid robot platforms

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    To precisely reach for an object with a humanoid robot, it is of central importance to have good knowledge of both end-effector, object pose and shape. In this work we propose a framework for markerless visual servoing on unknown objects, which is divided in four main parts: I) a least-squares minimization problem is formulated to find the volume of the object graspable by the robot's hand using its stereo vision; II) a recursive Bayesian filtering technique, based on Sequential Monte Carlo (SMC) filtering, estimates the 6D pose (position and orientation) of the robot's end-effector without the use of markers; III) a nonlinear constrained optimization problem is formulated to compute the desired graspable pose about the object; IV) an image-based visual servo control commands the robot's end-effector toward the desired pose. We demonstrate effectiveness and robustness of our approach with extensive experiments on the iCub humanoid robot platform, achieving real-time computation, smooth trajectories and sub-pixel precisions
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