Three-Dimensional Path-Following with Articulated 6DoF Robot and ToF Sensors
Source abstract
Abstract
This paper presents an algorithm for 3D path-following using an articulated 6-Degree-of-Freedom (DoF) robot as well as experimental verification of the proposed approach. This research extends the classic line-following concept, typically applied in 2D spaces, into a 3D space. This is achieved by equipping a standard industrial robot with a path detection tool featuring six low-cost Time-of-Flight (ToF) sensors. The primary objective is to enable the robot to follow a physically existing path defined in 3D space. The developed algorithm allows for step-by-step detection of the path’s orientation and calculation of consecutive positions and orientations of the detection tool that are necessary for the robot arm to follow the path. Experimental tests conducted using a Nachi MZ04D robot demonstrated the reliability and effectiveness of the proposed solution.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Robotic Path Planning Algorithms · Robotics and Sensor-Based Localization · Optimization and Search Problems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Mechanical Engineering and Ship Technology, Gdansk University of Technology, G. Narutowicza 11/12, 80-233 Gdansk, Poland
References (42)
Show source-provided references
1. Mobile robot’s path-planning and path-tracking in static and dynamic environments: Dynamic programming approach10.1016/j.robot.2023.104592 ↗
2. Namgung, H. (2022). Local Route Planning for Collision Avoidance of Maritime Autonomous Surface Ships in Compliance with COLREGs Rules. Sustainability, 14.10.3390/su14010198 ↗
3. Debnath, D., Vanegas, F., Sandino, J., Hawary, A.F., and Gonzalez, F. (2024). A Review of UAV Path-Planning Algorithms and Obstacle Avoidance Methods for Remote Sensing Applications. Remote Sens., 16.10.3390/rs16214019 ↗
4. Ou, X., You, Z., and He, X. (2024). Local Path Planner for Mobile Robot Considering Future Positions of Obstacles. Processes, 12.10.3390/pr12050984 ↗
5. Path planning techniques for mobile robots: Review and prospect10.1016/j.eswa.2023.120254 ↗
6. A Comprehensive Review of Coverage Path Planning in Robotics Using Classical and Heuristic Algorithms10.1109/ACCESS.2021.3108177 ↗
7. Thompson, N., Greenewald, K., Lee, K., and Manso, G.F. (2023, January 14–15). The Computational Limits of Deep Learning. Proceedings of the Ninth Computing within Limits 2023, Virtual.
8. Collision-free Autonomous Navigation of A Small UAV Using Low-cost Sensors in GPS-denied Environments10.1007/s12555-019-0797-7 ↗
9. (2024, December 18). Mekathlon—International Line Follower Robot Competition. Available online: https://www.mekathlon.com/fastest-line-follower.
10. (2024, December 18). Robotex International. Available online: https://robotex.international/line-following/.
11. Application of Multilayer Neural Networks for Controlling a Line-Following Robot in Robotic Competitions
12. Magnum Automation Inc. (2024, December 18). AGV/AGC Assembly Line. Available online: https://www.magnum-inc.com/systems/agvs-agcs/agc-assembly-line/.
13. Low-cost autonomous car level 2: Design and implementation for conventional vehicles10.1016/j.rineng.2023.100969 ↗
14. Lane Detection in Autonomous Vehicles: A Systematic Review10.1109/ACCESS.2023.3234442 ↗
15. Anand, M., Kalaisevi, P., Arun Kumar, S., and Nithyavathy, N. (2023, January 22–24). Design and Development of Automated Guided Vehicle with Line Follower Concept using IR. Proceedings of the 2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT), Erode, India.
16. Jang, J.-Y., Yoon, S.-J., and Lin, C.-H. (2023). Automated Guided Vehicle (AGV) Driving System Using Vision Sensor and Color Code. Electronics, 12.10.3390/electronics12061415 ↗
17. An Efficient Approach for Line-Following Automated Guided Vehicles Based on Fuzzy Inference Mechanism10.18196/jrc.v3i4.14787 ↗
18. Engin, M., and Engin, D. (2012, January 13–14). Path Planning of Line Follower Robot. Proceedings of the 5th European DSP Education and Research Conference (EDERC), Amsterdam, The Netherlands.10.1109/EDERC.2012.6532213 ↗
19. Real-time application of swarm and evolutionary algorithms for line follower automated guided vehicles: A comprehensive study10.1007/s12065-020-00496-4 ↗
20. Moshayedi, A.J., Zanjani, S.M., Xu, D., Chen, X., Wang, G., and Yang, S. (2022, January 28–29). Fusion based AGV Robot Navigation Solution Comparative Analysis and Vrep Simulation. Proceedings of the 8th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), Behshahr, Iran.10.1109/ICSPIS56952.2022.10044044 ↗
21. Learning visual path–following skills for industrial robot using deep reinforcement learning10.1007/s00170-022-09800-1 ↗
22. Manorathna, R.P., Phairatt, P., Ogun, P., Widjanarko, T., Chamberlain, M., Justham, L., Marimuthu, S., and Jackson, M.R. (2014, January 10–12). Feature extraction and tracking of a weld joint for adaptive robotic welding. Proceedings of the 13th International Conference on Control Automation Robotics & Vision (ICARCV), Singapore.10.1109/ICARCV.2014.7064515 ↗
23. (2024, December 18). Mathoworks Minidrone Competition. Available online: https://www.mathworks.com/academia/students/competitions/minidrones.html.
24. A UAV Guidance System Using Crop Row Detection and Line Follower Algorithms10.1007/s10846-019-01006-0 ↗
25. da Silva, Y.M.R., Andrade, F.A.A., Sousa, L., de Castro, G.G.R., Dias, J.T., Berger, G., Lima, J., and Pinto, M.F. (2022). Computer Vision Based Path Following for Autonomous Unmanned Aerial Systems in Unburied Pipeline Onshore Inspection. Drones, 6.10.3390/drones6120410 ↗
26. Autonomous power line detection and tracking system using UAVs10.1016/j.micpro.2022.104609 ↗
27. Pussente, G.A.N., de Aguiar, E.P., Marcato, A.L.M., and Pinto, M.F. (2023). UAV Power Line Tracking Control Based on a Type-2 Fuzzy-PID Approach. Robotics, 12.10.3390/robotics12020060 ↗
28. Xiang, X., Yu, C., Niu, Z., and Zhang, Q. (2016). Subsea Cable Tracking by Autonomous Underwater Vehicle with Magnetic Sensing Guidance. Sensors, 16.10.3390/s16081335 ↗
29. Application of unmanned USV surface and AUV underwater maritime platforms for the monitoring of offshore structures at sea
30. Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., and Sloot, P.M. (2021). Challenges Associated with Sensors and Data Fusion for AGV-Driven Smart Manufacturing. Computational Science—ICCS 2021, Springer. Lecture Notes in Computer Science.10.1007/978-3-030-77964-1 ↗
31. UAV path planning techniques: A survey10.1051/ro/2024073 ↗
32. ul Husnain, A., Mokhtar, N., Mohamed Shah, N., Dahari, M., and Iwahashi, M. (2023). A Systematic Literature Review (SLR) on Autonomous Path Planning of Unmanned Aerial Vehicles. Drones, 7.10.3390/drones7020118 ↗
33. Motion Planning for Industrial Robots using Reinforcement Learning10.1016/j.procir.2017.03.095 ↗
34. Progress, challenges and trends on vision sensing technologies in automatic/intelligent robotic welding: State-of-the-art review10.1016/j.rcim.2024.102767 ↗
35. A visual path-following learning approach for industrial robots using DRL10.1016/j.rcim.2021.102130 ↗
36. Slabaugh, G.G. (1999). Computing Euler Angles from a Rotation Matrix, Technical Report; University of London.
37. Nachi Fujikoshi Corp (2021). Manipulator Instruction Manual, MMZEN-288-013, Nachi Fujikoshi Corp.
38. ST Microelectronics (2025, February 13). VL6180X Proximity and Ambient Light Sensing (ALS) Module Datasheet, 2016. Available online: https://www.st.com/resource/en/datasheet/vl6180x.pdf.
39. Nachi Fujikoshi Corp (2021). CFDS Controller Instruction Manual User Task, CFDs-EN-123-001A, Nachi Fujikoshi Corp.
40. (2025, January 07). Mathworks, GeneralizedInverseKinematrics Object Documentation. Available online: https://www.mathworks.com/help/robotics/ref/generalizedinversekinematics-system-object.html.
41. Press, W.H., Teukolsky, S.A., Vetterling, W.T., and Flannery, B.P. (1992). Numerical Recipes in C, The Art of Scientific Computing, Cambridge University Press. [2nd ed.].
42. Liwiński, K., and Budzisz, D. (2024). Testing the Capabilities of the Nachi MZ04 Robot in Terms of Performing Tasks with External Control. [B.Sc. (Eng.) Thesis, Gdańsk University of Technology]. (In Polish).