IROS 2015 Paper Abstract


Paper ThCT7.3

Li, Shuai (RPI), Lyu, Siwei (SUNY Albany), Trinkle, Jeff (Rensselaer Polytechnic Institute), Burgard, Wolfram (University of Freiburg)

A Comparative Study of Contact Models for Contact-Aware State Estimation

Scheduled for presentation during the Regular session "Perception for Grasping and Manipulation 2" (ThCT7), Thursday, October 1, 2015, 11:50−12:05, Saal B3

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sept 28 - Oct 03, 2015, Congress Center Hamburg, Hamburg, Germany

This information is tentative and subject to change. Compiled on May 25, 2019

Keywords Perception for Grasping and Manipulation, Animation and Simulation, Dynamics


We study the contact-aware state estimation (CASE) problem, i.e., the problem of estimating the state of an object while it is being actively manipulated by a robot. Several researchers have developed particle filters for this problem. They estimate the state (pose and veocity) of manipulated objects, some physical properties (such as mass and shape), and contact information (such as, gain or loss of contact and transitions between sliding and sticking). However, the effects of various contact and noise models, which can have a huge impact on the estimation results, are obfuscated by implementation details. In this paper, we study the CASE problem arising from a simple pushing task with the goal of shedding light on the fundamental contact modeling choices. Specifically, we evaluate four particle filters based upon four probabilistic state transition models generated from a deterministic multibody dynamics models with rigid or compliant contacts, each of which is augmented by one of two different noise models. Comparisons of these state transition models are carried out through the analysis of real and simulated experiments, the results of which, provide guidance to filter designers.



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