Automatic Eye-in-Hand Calibration using EKF

TL;DR

This paper presents a self-calibration method for eye-in-hand robots using SLAM with EKF, enabling automatic estimation of camera-to-end-effector transformation based on workspace features.

Contribution

The paper introduces an EKF-based SLAM approach for automatic calibration of eye-in-hand robot systems using feature markers and intrinsic parameters.

Findings

Effective localization of camera and transformation estimation

Validated on UR5 robot with depth camera

Automatic calibration reduces manual effort

Abstract

In this paper, a self-calibration approach for eye-in-hand robots using SLAM is considered. The goal is to calibrate the positioning of a robotic arm, with a camera mounted on the end-effector automatically using a SLAM-based method like Extended Kalman Filter (EKF). Given the camera intrinsic parameters and a set of feature markers in a work-space, the camera extrinsic parameters are approximated. An EKF based measurement model is deployed to effectively localize the camera and compute the camera to end-effector transformation. The proposed approach is tested on a UR5 manipulator with a depth-camera mounted on the end-effector to validate our results.