Robotic Arm System with Computer Vision for Colour Object Sorting
DOI:
https://doi.org/10.14419/ijet.v7i4.27.22479Published:
2018-11-30Keywords:
Robotic Arm, Image Processing Technique, Forward Kinematic, Denavit-Hartenberg Algorithm, Modified Flower Pollination AlgorithmAbstract
This study presents the development of robotic arm with computer vision functionalities to recognise the objects with different colours, pick up the nearest target object and place it into particular location. In this paper, the overview of the robotic arm system is first presented. Then, the design of five-degrees of freedom (5-DOF) robotic arm is introduced, followed by the explanation of the image processing technique used to recognize the objects with different colours and obstacle detection. Next, the forward kinematic modelling of the robotic arm using Denavit-Hartenberg algorithm and solving the inverse kinematic of the robotic arm using modified flower pollination algorithm (MFPA) are interpreted. The result shows that the robotic arm can pick the target object accurately and place it in its particular place successfully. The concern on user safety is also been taken into consideration where the robotic arm will stop working when the user hand (obstacle) is detected and resume its process when there is no obstacle.
References
[1] Abdou, G., & Lee, E. (1991). "Physical model for robotics palletization. Computers in Industry", 16(3), 255–266. https://doi.org/10.1016/0166-3615(91)90063-F
[2] Almendral, K. A. M., Babaran, R. M. G., Carzon, B. J. C., Cu, K. P. K., Lalanto, J. M., & Abad, A. C. (2018). "Autonomous Fruit Harvester with Machine Vision. Journal of Telecommunication", Electronic and Computer Engineering, 10(1), 79–86. Retrieved from http://journal.utem.edu.my/index.php/jtec/article/view/3671/2554
[3] Artemiadis, P. K., Katsiaris, P. T., & Kyriakopoulos, K. J. (2010). "A biomimetic approach to inverse kinematics for a redundant robot arm. Autonomous Robots", 29(3-4), 293–308. https://doi.org/10.1007/s10514-010-9196-x
[4] Brunetti, A., Buongiorno, D., Trotta, G. F., & Bevilacqua, V. (2018). "Computer vision and deep learning techniques for pedestrian detection and tracking: A survey. Neurocomputing", 300, 17–33. https://doi.org/10.1016/j.neucom.2018.01.092
[5] Culler, D., & Long, J. (2016). "A Prototype Smart Materials Warehouse Application Implemented Using Custom Mobile Robots and Open Source Vision Technology Developed Using EmguCV". Procedia Manufacturing, 5, 1092–1106. https://doi.org/10.1016/j.promfg.2016.08.080
[6] Dharmannagari, V. K. R. (2014). "Sorting of Objects Based on Colour By Pick and Place Robotic Arm and With", 3(1).
[7] Dhepekar, P., & Adhav, Y. G. (2017). "Wireless robotic hand for remote operations using flex sensor. International Conference on Automatic Control and Dynamic Optimization Techniques, ICACDOT" 2016, 114–118. https://doi.org/10.1109/ICACDOT.2016.7877562
[8] Gu, J., Wang, H., Pan, Y., & Wu, Q. (2015). "Neural network based visual servo control for CNC load/unload manipulator". Optik, 126(23), 4489–4492. https://doi.org/10.1016/j.ijleo.2015.07.153
[9] Hayashi, S., Ota, T., Kubota, K., Ganno, K., & Kondo, N. (2005). "Robotic Harvesting Technology for Fruit Vegetables in Protected Horticultural Production. FRUTIC 05", Information and Technology for Sustainable Fruit and Vegetable Production, (September), 227–236.
[10] Lampert, C. H., Nickisch, H., & Harmeling, S. (2009)." Learning to detect unseen object classes by between-class attribute transfer". 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009, 2009 IEEE , 951–958. https://doi.org/10.1109/CVPRW.2009.5206594
[11] Li, S., Chen, S., Liu, B., Li, Y., & Liang, Y. (2012). "Decentralized kinematic control of a class of collaborative redundant manipulators via recurrent neural networks". Neurocomputing, 91, 1–10. https://doi.org/10.1016/j.neucom.2012.01.034
[12] Li, X., Qiao, T., Pang, Y., Zhang, H., & Yan, G. (2018). "A new machine vision real-time detection system for liquid impurities based on dynamic morphological characteristic analysis and machine learning. Measurement": Journal of the International Measurement Confederation, 124(October 2017), 130–137. https://doi.org/10.1016/j.measurement.2018.04.015
[13] Li, Y., Huang, T., & Chetwynd, D. G. (2018). "An approach for smooth trajectory planning of high-speed pick-and-place parallel robots using quintic B-splines". Mechanism and Machine Theory, 126, 479–490. https://doi.org/10.1016/j.mechmachtheory.2018.04.026
[14] Martinez-De Dios, J. R., & Ollero, A. (2015). "A learning-based thresholding method customizable to computer vision applications". Engineering Applications of Artificial Intelligence, 37, 71–90. https://doi.org/10.1016/j.engappai.2014.08.015
[15] Mehta, S. S. (2007). "Vision-Based Control for Autonomous Robotic Citrus Harvesting".
[16] Moghaddam, M., & Nof, S. Y. (2016). "Parallelism of Pick-and-Place operations by multi-gripper robotic arms". Robotics and Computer Integrated Manufacturing, 42, 135–146. https://doi.org/10.1016/j.rcim.2016.06.004
[17] Nearchou, A. C. (1998). "Solving the inverse kinematics problem of redundant robots operating in complex environments via a modified genetic algorithm""Application of Modified Flower Pollination Algorithm on Mechanical Engineering Design Problem. Batu Pahat, Johor.
[18] Rai, N., Rai, B., & Rai, P. (2014). "Computer Vision Approach for Controlling Educational Robotic Arm based on Object Properties" .
[19] Reddy, R., & Nagaraja, S. R. (2015). "Integration of robotic arm with vision system". 2014 IEEE International Conference on Computational Intelligence and Computing Research, IEEE ICCIC 2014, 373–378. https://doi.org/10.1109/ICCIC.2014.7238302
[20] Sajjad, M., Talpur, H., & Shaikh, M. H. (2012). "Automation of Mobile Pick and Place Robotic System for Small", 522–526.
[21] Sangeetha, G. R., Kumar, N., Hari, P. R., & Sasikumar, S. (2018). "Implementation of a Stereo vision based system for visual feedback control of Robotic Arm for space manipulations". Procedia Computer Science, 133, 1066–1073. https://doi.org/10.1016/j.procs.2018.07.031
[22] Saxena, a., Driemeyer, J., & Ng, a. Y. (2008). "Robotic Grasping of Novel Objects using Vision"". The International Journal of Robotics Research, 27(2), 157–173. https://doi.org/10.1177/0278364907087172
[23] Starke, S. (2016). "A Hybrid Genetic Swarm Algorithm for Interactive Inverse Kinematics". MSc Thesis.
[24] Taylor, P. (2007). "On Optimizing Bin Picking and Insertion Plans for Assembly Robots On Optimizing Bin Picking and Insertion" Plans for Assembly Robots, (December 2013), 37–41.
[25] Zhang, Y., & Wang, J. (2004). "Obstacle Avoidance for Kinematically Redundant Manipulators Using a Dual Neural Network", 34(1), 752–759.
View Full Article:
How to Cite
License
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution Licensethat allows others to share the work with an acknowledgement of the work''s authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal''s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Accepted 2018-11-30
Published 2018-11-30