Active learning with query paths for tactile object shape exploration

In the present work, we propose an active learning framework based on optimal query paths to efficiently address the problem of tactile object shape exploration. Most previous approaches perform active touch probing at discrete query points, which leads to inefficient touch-and-retract motions. In contrast, in this paper we propose to query information efficient sliding paths instead of only touch locations. This is realized by three components: A Gaussian process implicit surface model represents the shape and uncertainty of the object. A compliant task/force controller framework fuses the information of this GP model into the parameterization of its tasks, which enables the robot to slide over the unknown object safely and robustly. Thirdly, we develop two strategies to solve the proposed active path querying learning problem. Sliding along those query paths not only creates more dense data than touch probing, but additionally greatly reduces the uncertainty of the object. We demonstrate the effectiveness of our proposed framework both in simulation and on the PR2 robot platform. Furthermore, it is shown that our methodology can be extended to other learning tasks, such as finding a desired surface normal on an unknown object, e. g. for pushing.

Authors

• Danny Driess
• Peter Englert
• Marc Toussaint

Keywords

• Surface treatment
• Shape
• Robot sensing systems
• Uncertainty
• Data models
• Gaussian processes
• Active Learning
• Object Shape
• Query Path
• Surface Model
• Gaussian Process
• Optimal Path
• Gaussian Process Model
• Unknown Objects
• Query Point
• Surface Normals
• Optimization Problem
• Measurement Uncertainty
• Global Strategy
• Simulation Approach
• Path Planning
• Joint Space
• Tactile Sensor
• Acquisition Function
• Surface Representation
• Exploration Strategy
• Greedy Strategy
• Task Space
• Tangent Plane
• Real Robot
• Marching Cubes Algorithm
• Reference Velocity
• Travel Length
• Concept Of Control
• Tangent Space
• Touchpoints