Ruehr, Thomas (Technische Universitaet Muenchen), Sturm, Jürgen (Technical University of Munich), Pangercic, Dejan (TU Muenchen), Beetz, Michael (Technische Universität München), Cremers, Daniel (Technical University of Munich)

A Generalized Framework for Opening Doors and Drawers in Kitchen Environments

Scheduled for presentation during the Regular Session "Intelligent Manipulation Grasping" (ThA06), Thursday, May 17, 2012, 08:30−08:45, Meeting Room 6 (Oya'te)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on September 23, 2021

Abstract

In this paper, we present a generalized framework for robustly operating previously unknown cabinets in kitchen environments. Our framework consists of the following four components: (1) a module for detecting both Lambertian and non-Lambertian (i.e. specular) handles, (2) a module for opening and closing novel cabinets using impedance control and for learning their kinematic models, (3) a module for storing and retrieving information about these objects in the map, and (4) a module for reliably operating cabinets of which the kinematic model is known. The presented work is the result of a collaboration of three PR2 beta sites. We rigorously evaluated our approach on 29 cabinets in five real kitchens located at our institutions. These kitchens contained 13 drawers, 12 doors, 2 refrigerators and 2 dishwashers. We evaluated the overall performance of detecting the handle of a novel cabinet, operating it and storing its model in a semantic map. We found that our approach was successful in 51.9% of all 104 trials. With this work, we contribute a well-tested building block of open-source software for future robotic service applications.