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Titlebook: RiTA 2020; Proceedings of the 8 Esyin Chew,Anwar P. P. Abdul Majeed,Jong-Hwan Kim Conference proceedings 2021 The Editor(s) (if applicable)

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樓主: 小故障
51#
發(fā)表于 2025-3-30 11:08:18 | 只看該作者
52#
發(fā)表于 2025-3-30 15:16:43 | 只看該作者
Conference proceedings 2021Learning, Mobile Robotics, Social Robotics and Humanoid Robotics, Sensors and Actuators, and Machine Vision, as well as Signal and Image Processing. As a valuable asset, the book offers researchers and practitioners a timely overview of the latest advances in robot intelligence technology and its applications..
53#
發(fā)表于 2025-3-30 17:06:41 | 只看該作者
2195-4356 on Robot Intelligence Technology and Applications, 2020.Inc.This book gathers the Proceedings of the 8th International Conference on Robot Intelligence Technology and Applications (RITA 2020).? The areas covered include: Instrumentation and Control, Automation, Autonomous Systems, Biomechatronics a
54#
發(fā)表于 2025-3-30 20:54:41 | 只看該作者
55#
發(fā)表于 2025-3-31 02:22:41 | 只看該作者
Drone Swarm Operating and Monitoring System for States Error Compensation,s a lot of problems with rtk-gps, magnetometer noise, RF/ESC noise, and motor vibration. For these reasons, there are cases where state estimation is not properly performed. In this paper, therefore, we propose a system that can perform swarm flight using such a small drone, monitor the state error of each drone, and correct it.
56#
發(fā)表于 2025-3-31 08:05:39 | 只看該作者
Conference proceedings 2021ed include: Instrumentation and Control, Automation, Autonomous Systems, Biomechatronics and Rehabilitation Engineering, Intelligent Systems, Machine Learning, Mobile Robotics, Social Robotics and Humanoid Robotics, Sensors and Actuators, and Machine Vision, as well as Signal and Image Processing. A
57#
發(fā)表于 2025-3-31 11:53:10 | 只看該作者
58#
發(fā)表于 2025-3-31 13:58:43 | 只看該作者
59#
發(fā)表于 2025-3-31 20:19:13 | 只看該作者
Human-Like Control System Design of the Lower Limb Rehabilitation Robot Based on Adaptive RBF Neurah the human kinematics characteristics. To improve the tracking accuracy, the ARBF neural network controller is adopted estimate the model uncertain parameters. Simulation results demonstrate the effectiveness of the proposed method.
60#
發(fā)表于 2025-3-31 22:14:20 | 只看該作者
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