Estimating Door Shape and Manipulation Model for Daily Assistive Robots Based on the Integration of Visual and Touch Information

Abstract

We propose a method for a robot to manipulate an unknown door based on a single user instruction. The primary contributions of this paper are (i) to reduce the user instruction to a single click and (ii) to develop an efficient method to estimate an appropriate shape and manipulation model for a target door by integrating visual and touch information obtained by a robot. The proposed method first detects door candidates using a 3-D camera and then estimates the manipulation model of each candidate based on prior learning results. During door manipulation, the system integrates visual and touch information to estimate the shape and manipulation model to generate an appropriate motion. We evaluated the proposed method experimentally, and the results prove that the proposed method is effective.