Video for pick&place study in AFRC project. [Dataset]

Abstract

In order to extend the abilities of current robots in industrial applications towards more autonomous and flexible manufacturing, this work presents an integrated system comprising real-time sensing, path-planning and control of industrial robots to provide them with adaptive reasoning, autonomous thinking and environment interaction under dynamic and challenging conditions. The developed system consists of an intelligent motion planner for a 6 degrees-of-freedom robotic manipulator, which performs pick-and-place tasks according to an optimized path computed in real-time while avoiding a moving obstacle in the workspace. This moving obstacle is tracked by a sensing strategy based on machine vision, working on the HSV space for color detection in order to deal with changing conditions including non-uniform background, lighting reflections and shadows projection. The proposed machine vision is implemented by an off-board scheme with two low-cost cameras, where the second camera is aimed at solving the problem of vision obstruction when the robot invades the field of view of the main sensor. Real-time performance of the overall system has been experimentally tested, using a KUKA KR90 R3100 robot. A machine vision module based on low-cost cameras and color detection in the hue, saturation, value (HSV) space is developed to make the robot aware of its changing environment. Therefore, this vision allows the detection and localization of a randomly moving obstacle. Path correction to avoid collision avoidance for such obstacles with robotic manipulator is achieved by exploiting an adaptive path planning module along with a dedicated robot control module, where the three modules run simultaneously. These sensing/smart capabilities allow the smooth interactions between the robot and its dynamic environment, where the robot needs to react to dynamic changes through autonomous thinking and reasoning with the reaction times below the average human reaction time. The experimental results demonstrate that effective human-robot and robot-robot interactions can be realized through the innovative integration of emerging sensing techniques, efficient planning algorithms and systematic designs.

Citation

YAN, Y., ZABALZA, J., MINEO, C., YANG, E., FEI, Z. and WANG, C. 2019. Video for pick&place study in AFRC project. [Dataset]. Hosted on Pureportal (University Strathclyde) [online]. Available from: https://doi.org/10.15129/4df22803-2cc4-4cce-9cea-509f88f1b504

• Acceptance Date: Mar 5, 2019
• Online Publication Date: Mar 5, 2019
• Publication Date: Mar 5, 2019
• Deposit Date: Jun 21, 2022
• Publicly Available Date: Jun 21, 2022
• Publisher: University of Strathclyde
• DOI: https://doi.org/10.15129/4df22803-2cc4-4cce-9cea-509f88f1b504
• Keywords: Industrial robots; Robots; Cameras; Real time systems; Motion planning
• Public URL: https://rgu-repository.worktribe.com/output/1654209
• Related Public URLs: https://rgu-repository.worktribe.com/output/1085403; https://rgu-repository.worktribe.com/output/1654258
• Type of Data: 2 MP4 video files.
• Collection Date: Mar 31, 2018
• Collection Method: This data contains two video files in MP4 format that was created for the demo of pick&place study in AFRC (Advanced Forming Research Centre) project. It quite clearly shows the robot adapting to the sudden appearance of the obstacle.