SCARA Self Posture Recognition Using a Monocular Camera

Abstract

Robotic manipulators rely on feedback obtained from rotary encoders for control purposes. This article introduces a vision-based feedback system that can be used in an agricultural context, where the shapes and sizes of fruits are uncertain. We aim to mimic a human, using vision and touch as manipulator control feedback. This work explores the use of a fish-eye lens camera to track a SCARA manipulator with coloured markers on its joints for the position estimation with the goal to reduce costs and increase reliability. The Kalman Filter and the Particle Filter are compared and evaluated in terms of accuracy and tracking abilities of the marker's positions. The estimated image coordinates of the markers are converted to world coordinates using planar homography, as the SCARA manipulator has co-planar joints and the coloured markers share the same plane. Three laboratory experiments were conducted to evaluate the system's performance in joint angle estimation of a manipulator. The obtained results are promising, for future cost effective agricultural robotic arms developments. Besides, this work presents solutions and future directions to increase the joint position estimation accuracy.

Pose Determination System for a Serial Robot Manipulator Based on Artificial Neural Networks

“…Due to the robustness of the proposed approach, it can be used for agricultural purposes, as shown in [3]. Moreover, it does not require any specific color marker or orientation because once deployed and trained, the proposed approach can be used with a variety of different light intensities.…”

“…The system's output is the angle of each robot joint, which can be used to determine the pose of the end effector. This method is more robust than others such as Perspective n Point because it does not depend on a specific marker [35] or need specific light conditions [3]. Moreover, this method can be used in circumstances where the robot is partially occluded, with promising results.…”

“…[2]. On manipulator startup, the system assumes that the manipulator's joints are in the same angular position as they were on shutdown, which is not necessarily true due to malfunctions in incremental rotary encoders [3]. Robots are calibrated using laser probes and stereo cameras, and a specialized setup is necessary.…”

“…To simulate the pose-estimation process, a measurement system was established with a common camera and marker. In [3], the authors proposed a system comprising a SCARA manipulator, a Raspberry Pi camera, a fish eye lens, and colored markers (painted spheres), which was able to estimate joint angles with some errors. For marker tracking, a Kalman filter and particle filter were combined and used to estimate homography matrix world coordinates.…”