Open Access
| Issue |
EPJ Web Conf.
Volume 344, 2025
AI-Integrated Physics, Technology, and Engineering Conference (AIPTEC 2025)
|
|
|---|---|---|
| Article Number | 01062 | |
| Number of page(s) | 11 | |
| Section | AI-Integrated Physics, Technology, and Engineering | |
| DOI | https://doi.org/10.1051/epjconf/202534401062 | |
| Published online | 22 December 2025 | |
- A. W. Utomo, Transisi agraris ke industri (studi sosiologis perubahan sosial: transisi masyarakat agraris ke industri di Dusun Timang, Wonokerto, Kabupaten Wonogiri). Jurnal Cakrawala. 7, 2, 205–230 (2018) [Google Scholar]
- R. A. Ramadhani, G. Jati, W. Jatmiko, A. Y. Husodo, Adaptive multi-strategy observation of kernelized correlation filter for visual object tracking. Proc. Asia-Pacific Conf. Intell. Robot Syst. (ACIRS). 134–139 (2019). https://doi.org/10.1109/ACIRS.2019.8936042 [Google Scholar]
- F. Guangyuan, W. Ming, H. Shuai, F. Wenyu, W. Xiangyao, Object tracking algorithm based on better parallax of monocular under unknown environment. Proc. Int. Comput. Signals Syst. Conf. (ICOMSSC). 830–834 (2018). https://doi.org/10.1109/ICOMSSC45026.2018.894 1967 [Google Scholar]
- T. S. Dewi, R. Mardiati, L. Kamelia, A. E. Setiawan, Yumna, R. Rustandi, Prototype of mobile robot tracking object using sensor vision. Proc. Int. Conf. Wireless Telematics (ICWT). 1–5 (2022). https://doi.org/10.1109/ICWT55831.2022.9935442 [Google Scholar]
- C. Chen,et al., A real-time motion detection and object tracking framework for future robot-rat interaction. Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst. (IROS). 7404–7409 (2021). https://doi.org/10.1109/IROS51168.2021.9636403 [Google Scholar]
- D. Han, Y. Peng, Human-following of mobile robots based on object tracking and depth vision. Proc. Int. Conf. Mechatronics Robotics Autom. (ICMRA). 105–109 (2020). https://doi.org/10.1109/ICMRA51221.2020.93983 66 [Google Scholar]
- Y. Liu, Y. Zheng, L. Han, J. Liu, Z. Pan, F. Sun, The moving target recognition and tracking using RGB-D data with the mobile robot. Proc. Chinese Control Conf. (CCC). 4342–4347 (2019). https://doi.org/10.23919/ChiCC.2019.8865493 [Google Scholar]
- N. Guo, X. Zhang, Y. Zou, B. Lenzo, T. Zhang, A computationally efficient path-following control strategy of autonomous electric vehicles with yaw motion stabilization. IEEE Trans. Transp. Electrification. 6, 2, 728–739 (2020). https://doi.org/10.1109/TTE.2020.2993862 [Google Scholar]
- S. Lai, M. Lan, B. M. Chen, Model predictive local motion planning with boundary state constrained primitives. IEEE Robot Autom Lett. 4, 4, 3577–3584 (2019). https://doi.org/10.1109/LRA.2019.2928255 [Google Scholar]
- Y. Chen, B. Chu, C. T. Freeman, Iterative learning control for robotic path following with trial-varying motion profiles. IEEE/ASME Trans. Mechatronics. 27, 6, 4697–4706 (2022). https://doi.org/10.1109/TMECH.2022.3164101 [Google Scholar]
- M. Latif, S. Hardi, S. Herawati, Motion control development for autonomous ground robots in agriculture task. J Phys Conf Ser. 2193(1), 012060 (2022). https://doi.org/10.1088/1742-6596/2193/1/012060 [Google Scholar]
- M. K. Mishra, A. K. Samantaray, G. Chakraborty, Joint-space kinematic control of a bionic continuum manipulator in real-time by using hybrid approach. IEEE Access. 10, 47031–47050 (2022). https://doi.org/10.1109/ACCESS.2022.3171236 [Google Scholar]
- A. Singletary, S. Kolathaya, A. D. Ames, Safety- critical kinematic control of robotic systems. IEEE Control Syst Lett. 6, 139–144 (2022). https://doi.org/10.1109/LCSYS.2021.3050609 [Google Scholar]
- N. Tan, P. Yu, Z. Zhong, F. Ni, A new noise- tolerant dual-neural-network scheme for robust kinematic control of robotic arms with unknown models. IEEE/CAA J Automatica Sinica. 9, 10, 1778–1791 (2022). https://doi.org/10.1109/JAS.2022.105869 [Google Scholar]
- M. M. Marinho, B. V. Adorno, Adaptive constrained kinematic control using partial or complete task-space measurements. IEEE Trans. Robot. 38, 6, 3498–3513 (2022). https://doi.org/10.1109/TRO.2022.3181047 [Google Scholar]
- L. Tang, F. Yan, B. Zou, K. Wang, C. Lv, An improved kinematic model predictive control for high-speed path tracking of autonomous vehicles. IEEE Access. 8, 51400–51413 (2020). https://doi.org/10.1109/ACCESS.2020.2980188 [Google Scholar]
- J. Fan, L. Jin, Z. Xie, S. Li, Y. Zheng, Data-driven motion-force control scheme for redundant manipulators: A kinematic perspective. IEEE Trans. Ind. Inform. 18, 8, 5338–5347 (2022). https://doi.org/10.1109/TII.2021.3125449 [Google Scholar]
- R. Kazemian, S. Nahavandi, R. D. Saddik, Vision- based tracking control for mobile robot navigation. IEEE Access. 9, 17782–17793 (2021). https://doi.org/10.1109/ACCESS.2021.3054843 [Google Scholar]
- M. Zhu, K. Hauser, Real-time camera-based robot navigation using visual odometry. Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst. (IROS). 11465– 11472 (2020). https://doi.org/10.1109/IROS45743.2020.9341270 [Google Scholar]
- A. S. F. M. Ashraf, M. S. Uddin, J. Shin, Path- following control for autonomous mobile robots using kinematic modeling. IEEE Access. 8, 94448–94460 (2020). https://doi.org/10.1109/ACCESS.2020.2995979 [Google Scholar]
- S. Kamble, A. Raina, Autonomous mobile robot navigation using deep visual perception. Proc. IEEE Int. Conf. Robot. Autom. (ICRA). 4450–4456 (2021). https://doi.org/10.1109/ICRA48506.2021.9560983 [Google Scholar]
- C. L. Teo, B. M. Chen, Vision-guided autonomous mobile robot navigation using image-based visual servoing. Proc. IEEE Int. Conf. Robot. Autom. (ICRA). 1022–1028 (2021). https://doi.org/10.1109/ICRA48506.2021.9561117 [Google Scholar]
- A. H. Abdulhafez, S. Kamel, Real-time vision- based detection and tracking for mobile robot navigation. IEEE Access. 9, 11892–11905 (2021). https://doi.org/10.1109/ACCESS.2021.3050864 [Google Scholar]
- M. S. Mahmoud, H. Abouelnaga, Visual servoing- based mobile robot motion tracking under uncertain environments. IEEE Access. 10, 58472–58484 (2022). https://doi.org/10.1109/ACCESS.2022.3181574 [Google Scholar]
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