Research

Development of a Virtual Force Sensor for a Low-Cost Collaborative Robot and Applications to Safety Control

Developer: Shih-Hsiang Yen

This study proposes a low-cost, sensor less rigid robot arm design that employs a virtual force sensor and stiffness control to enable the safety collision detection and low-precision force control of robot arms. In this design, when a robot arm is subjected to an external force while in motion, the contact force observer estimates the external torques on each joint according to the motor electric current and calculation errors of the system model, which are then used to estimate the external contact force exerted on the robot arm's end-effector. Additionally, a torque saturation limiter is added to the servo drive for each axis to enable the real-time adjustment of joint torque output according to the estimated external force, regulation of system stiffness, and achievement of impedance control that can be applied in safety measures and force control. The design this study developed is a departure from the conventional multi sensor flexible mechanism approach. Moreover, it is a low-cost and sensor less design that relies on model-based control for stiffness regulation, there by improving the safety and force control in robot arm applications.

CAD-based Offline Programming Platform for Industrial Robot-based Automation

Developer: Amit Bedaka

In manufacturing processes, programming robotic systems is a time-consuming, difficult and costly exercise, especially for small and medium-sized enterprises (SMEs). In this direction, many solutions have been proposed, to benefit with existing offline programming (OLP) software one needs to have a license. Further, the architecture of existing OLP solutions is rigid to modify or update with applications requirement. The goal of this research is to design and develop a customizable application-oriented offline programming (OLP) platform with flexible architecture, which allows integrate with other systems to generate novel systems. The core idea involves integrating CAD and robotics information to design and develop a virtual platform for 3D model importation, path planning, pose visualization, and robot script generation and modification within the same environment. The proposed approach based on OPEN CASCADE (OCC) open source libraries, which allow the users to independently develop and directly generate a robot path from CAD models. The platform fully utilizes geometric information from both the 3D object and the machine tool embedded in the CAD models and transforms them into the robot path required for an assigned task. This proposed platform offers friendly interaction in an intuitive way so that in a few minutes, any user can generate a robot path and visualize the simulation graphically. In addition, this innovative platform can help many industries achieve a higher level of intelligent automation and increase quality while reducing the cost of production.

--------------Past Projects--------------

Automatic camera calibration and image based object positioning systems based on 6-axis robot arm

Developer: Shao-Chun Li

This research provides two solutions to solve two exist problems in the automated production process. Firstly, we provide a solution to improve the efficiency and accuracy of a manual camera calibration process by using a robot-arm operated automatic calibration procedure. With the robot arm holding the camera in a predefined positions and orientation to take the pictures on the calibration board and calibrate the camera intrinsic parameters, the lens distortion parameters and hand-eye transform matrix at the same time in a fully autonomous manner. Secondly, in order to tackle the difficulty resulted from poor object positioning situations in the automated production process, we develop a new solution by attaching some artificial landmarks on the target object and using the camera system to perform the calibration based on the image containing the landmarks. In the case that the object has some position errors, the system can compute the compensation displacement needed by the robot arm by comparison of the two images of the artificial land marks. The results in the experiments show both systems have successfully shown high performance, high accuracy and high implementation potential.

Development of 6-axis Robot Autonomous Line Tracking and Following System

Developer: Tsung-En Hsieh

The purpose of this study is to develop a 6-axis Robot Autonomous Line Tracking and Following System with three line lasers and a camera. The system can autonomously follow and track a 3D line and thereby conduct some processing by robot arm without time-consuming teaching tack. In the autonomous line tracking system, we must conduct some calibration. First,we need to perform camera calibration. Second, let the camera plane be parallel to the working space, which is the same plane with the check board. Then project a line laser on the working space and take images in different depths of camera and working space for calibrating the relationship of the line laser and the camera. By there lationship between the line laser and the camera, the calibration performed on each line laser can get three equations to calculate the depth of the camera and the working area. By calibration of the camera and the tool coordinate, the vision system can connect to the robot arm to conduct some processing on the line tracking.Some experiments are conducted to prove the system accuracy, on the three-axisrotation calculate errors, the work point deviation in 3D space, and the gluing result deviation.In the three-axis rotation calculation error analysis, only the work on one axis is independently conducted in each experiment. To take the image on the check board indifference angle, we can get the system slope in the 3D space. By comparing two values from the check board and the vision system, we can get the three-axis rotation calculation error.On the work point deviation analysis, we need to generate the 3D model of a line in 3D space. Using the tracking system to scan the line to get the work points. After comparing the value of the 3D model and the real work points, we can calculate the deviation between the work points and the track line.In the gluing experiment, we can compare the gluing result and the track line sample to get the deviation of the gluing accuracy.

Pallet Box Autonomous Relocation System

Developer: Hsuan-Hung Chou

This study develops an autonomous pallet boxes relocation system that can fully automatically download boxes on the pallet and then relocate the boxes to designated locations. The system is based on the motion capability of a large robot arm and the computer vision modules that enable autonomous operation. The system comprises two sets of vision modules, one is Kinect v2 and the other is the stereo camera system, to serve in different workspace and requirement. The vision detection techniques developed in this system combine 2D image processing codes, and the points cloud algorithm. For detecting boxes with pattern surfaces, we use ORB(Oriented FAST and rotated BRIEF) feature detection and match template image features to the detected image so as to determine the box position and rotation. In order to determine the correct box position, we use RANSAC(Random sample consensus) and Homography matrix. For boxes without pattern features, we combine the 2D line detection to find the edge line of the box and remove the points on the edge line. After that, 3D clustering and OBB(Oriented bounding box, OBB)are implemented to obtain the precious positions of boxes and pallets. Then system will automatically calculate the path of the robot arm to pick the boxes and download them. In this system, there are three path planning options: first is to duplicate the stacking formation of the boxes on the original pallet to a new pallet, second is to allow the user to select the stacking pattern on a specific floor area, and third is to allow the user to define the size and the position of the target floor area, and the system will perform the optimized stacking pattern to save the space and time. The experiments have proven the system effective and precise, and with high commercial values.