Body Schema Learning

  title={Body Schema Learning},
  author={J{\"u}rgen Sturm and Christian Plagemann and Wolfram Burgard},
  booktitle={Towards Service Robots for Everyday Environments},
Kinematic models are widely used in robotics to describe the mechanism of a robot. For example, the kinematic model of a manipulation robot is typically specified by the position of its joints, and the size and orientation of its links (Craig, 1989; Sciavicco and Siciliano, 2000). Kinematic models are usually derived analytically by a robot engineer and thus rely heavily on prior knowledge about the geometry of the robot. When such a model is applied to a real robot, its parameters have to be… 

Bootstrapping bilinear models of Simple Vehicles

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Sensorimotor Learning for an Artificial Body Schema on Humanoid Robots

zur Erlangung des akademischen Grades eines Doktors der Ingenieurwissenschaften der Fakultat fur Informatik des Karlsruher Instituts fur Technologie (KIT).

Robot End Effector Tracking Using Predictive Multisensory Integration

A biologically inspired model that enables a humanoid robot to learn how to track its end effector by integrating visual and proprioceptive cues as it interacts with the environment is proposed, which has properties that are qualitatively similar to the characteristics of human eye-hand coordination.



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Learning inverse kinematics

  • Aaron D'SouzaS. VijayakumarS. Schaal
  • Mathematics
    Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180)
  • 2001
This paper investigates inverse kinematics learning for resolved motion rate control (RMRC) employing an optimization criterion to resolve kinematic redundancies and demonstrates how a recently developed statistical learning algorithm, locally weighted projection regression, allows efficient learning of inverse k Cinematic mappings in an incremental fashion even when input spaces become rather high dimensional.

Calibrating a Multi-arm Multi-sensor Robot: A Bundle Adjustment Approach

An extendable framework that combines measurements from the robot's various sensors (proprioceptive and external) to calibrate the robot’s joint offsets and external sensor locations is proposed, allowing sensors with very different error characteristics to be used side by side in the calibration.

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The body representations in biology is surveyed from a functional or computational perspective to set ground for a review of the concept of body schema in robotics and identifies trends in these research areas and proposes future research directions.

Efficient exploration and learning of whole body kinematics

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Adaptive body schema for robotic tool-use

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