Pose Estimation of a Container with Contact Sensing Based on Discrete State Discrimination

Abstract

In cases where vision is not sufficiently reliable for robots to recognize an object, tactile sensing can be a promising alternative for estimating the object’s pose. In this paper, we consider the task of a robot estimating the pose of a container aperture in order to select an object. In such a task, if the robot can determine whether its hand with equipped contact sensor is inside or outside the container, estimation of the object’s pose can be improved by reflecting the discrimination to the robotic hand’s exploration strategy. We propose an exploration strategy and an estimation method using discrete state recognition on the basis of a particle filter. The proposed method achieves superior estimation in terms of the number of contact actions, operation time, and stability of estimation efficiency. The pose is estimated with sufficient accuracy that the hand can be inserted into the container.