Automatic and self-contained calibration of a multi-sensorial humanoid's upper body

Birbach, Oliver; Bäuml, Berthold; Frese, Udo

doi:10.1109/icra.2012.6225004

Cited by 20 publications

(19 citation statements)

References 22 publications

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“…For instance, the method used by Birbach et al (2012) requires 5 min of data acquisition during specific robot movements with a special marker in the robot wrist. It optimizes offline some parameters of the kinematic chain (angle offsets and elasticity) of an upper humanoid torso using nonlinear least squares.…”

Section: Related Workmentioning

confidence: 99%

Online Body Schema Adaptation Based on Internal Mental Simulation and Multisensory Feedback

2016

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In this paper, we describe a novel approach to obtain automatic adaptation of the robot body schema and to improve the robot perceptual and motor skills based on this body knowledge. Predictions obtained through a mental simulation of the body are combined with the real sensory feedback to achieve two objectives simultaneously: body schema adaptation and markerless 6D hand pose estimation. The body schema consists of a computer graphics simulation of the robot, which includes the arm and head kinematics (adapted online during the movements) and an appearance model of the hand shape and texture. The mental simulation process generates predictions on how the hand will appear in the robot camera images, based on the body schema and the proprioceptive information (i.e., motor encoders). These predictions are compared to the actual images using sequential Monte Carlo techniques to feed a particle-based Bayesian estimation method to estimate the parameters of the body schema. The updated body schema will improve the estimates of the 6D hand pose, which is then used in a closed-loop control scheme (i.e., visual servoing), enabling precise reaching. We report experiments with the iCub humanoid robot that support the validity of our approach. A number of simulations with precise ground-truth were performed to evaluate the estimation capabilities of the proposed framework. Then, we show how the use of high-performance GPU programing and an edge-based algorithm for visual perception allow for real-time implementation in real-world scenarios.

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Section: Related Workmentioning

confidence: 99%

Online Body Schema Adaptation Based on Internal Mental Simulation and Multisensory Feedback

2016

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“…They tune joint angle offsets and the relative pose of the sensors in the attachment links with a maximum likelihood approach that considers measurement uncertainties. Birbach et al [2] calibrate the intrinsic parameters of both cameras, their frames relative to the head, an inertial measurement unit in the head, and the joint angle offsets and elasticities of the hand-head chains of the robot Rollin' Justin. They observe a point marker on the wrist with the stereo cameras in the head.…”

Section: Related Workmentioning

confidence: 99%

“…Like in many other approaches (e.g., [1], [2]), our robots perceive visual markers attached to their bodies for the calibration. These measured poses are compared to the expected poses of the end-effector according to a parametric model of the hand-eye kinematics.…”

Section: Introductionmentioning

confidence: 99%

Bayesian calibration of the hand-eye kinematics of an anthropomorphic robot

Hubert

Stückler

Behnke

2012

2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012)

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Abstract-We present a Bayesian approach to calibrating the hand-eye kinematics of an anthropomorphic robot. In our approach, the robot perceives the pose of its end-effector with its head-mounted camera through visual markers attached to its end-effector. It collects training observations at several configurations of its 7-DoF arm and 2-DoF neck which are subsequently used for an optimization in a batch process. We tune Denavit-Hartenberg parameters and joint gear reductions as a minimal representation of the rigid kinematic chain. In order to handle the uncertainties of marker pose estimates and joint position measurements, we use a maximum a posteriori formulation that allows for incorporating prior model knowledge. This way, a multitude of parameters can be optimized from only few observations. We demonstrate our approach in simulation experiments and with a real robot and provide indepth experimental analysis of our optimization approach.

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“…An example of this trend is Birbach et al [1], who proposed to calibrate a humanoid upper-body equipped with heterogeneous sensors, such as stereo cameras and an IMU, in an automatic and self-contained fashion by observing a marker on the robot's wrist while performing H. Carrillo Which configuration should we use for calibration? The figure depicts three plausible robot configurations for an automatic and self contained calibration task.…”

Section: Introductionmentioning

confidence: 98%

On task-oriented criteria for configurations selection in robot calibration

Carrillo

Birbach

Täubig

et al. 2013

2013 IEEE International Conference on Robotics and Automation

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This paper studies different criteria for selecting configurations for the task of calibrating a robotic system. Given an automatic and self-contained procedure which allows the robot to calibrate itself without the need of external tools, we are interested in how to select the set of configurations that maximize calibration accuracy while minimizing calibration time. We experiment with the active calibration of a multi sensorial humanoid's upper body and report that determinant based criteria should be preferred when a greedy selection is used. In addition to criteria comparison, we further propose a new criterion for configuration selection. Its novelty stems from a direct treatment of the robot's end-effector tool variance. This is contrary to previous approaches which target the variance indirectly via calibration parameters. Our proposed objective function is derived as a compact formulation from the mean error of the robot's end-effector tool from which its variance can be computed using traditional criteria known from the theory of optimal experimental design (e.g. A-optimality).

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Automatic and self-contained calibration of a multi-sensorial humanoid's upper body

Cited by 20 publications

References 22 publications

Online Body Schema Adaptation Based on Internal Mental Simulation and Multisensory Feedback

Online Body Schema Adaptation Based on Internal Mental Simulation and Multisensory Feedback

Bayesian calibration of the hand-eye kinematics of an anthropomorphic robot

On task-oriented criteria for configurations selection in robot calibration

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