Jianxiong Hao is a researcher specializing in the development of shape and force perception and control technologies for continuum and soft robots. Currently pursuing his Master’s and Doctoral degrees in Mechanical Engineering at Tianjin University, he has contributed significantly to medical robotic systems, particularly focusing on soft manipulators used in surgery. Hao’s work addresses key challenges such as accurate shape and force feedback, adaptive control, and the application of machine learning techniques to improve the performance and versatility of these robots. His research is pushing the boundaries of robotics, offering promising solutions for complex, real-world applications.
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Jianxiong Hao is a researcher at Tianjin University, China, with a focus on continuum and soft robotics, particularly in the areas of shape and force perception and control. Hao has contributed significantly to the field with 40 documents cited 44 times, showcasing his impact in robotics research. His work has been featured in high-impact journals, with notable publications on topics such as shape estimation, force sensing, and adaptive control for medical robots. Hao’s contributions continue to influence the development of advanced robotics systems, particularly those used in medical applications. His h-index of 5 reflects his growing academic presence and the significance of his research.
Education
Jianxiong Hao completed his Bachelor’s degree in Machine Design, Manufacture, and Automation at Tianjin University in June 2020. He is currently enrolled in the Master’s and Doctoral program in Mechanical Engineering at Tianjin University, where his research focuses on continuum and soft robots. His academic journey has been shaped by a deep interest in robotics, control systems, and machine learning, positioning him as a rising expert in the field of soft robotics with applications in medical and industrial settings.
Research Focus
Hao’s research is focused on the development of advanced shape and force perception and control systems for continuum and soft robots. He aims to solve key challenges in medical robotics, including achieving accurate shape and force feedback and improving control stability and adaptability in complex, unstructured environments. His work incorporates model-free adaptive control methods, machine learning techniques, and multi-sensing systems to enhance the robustness of continuum manipulators. These innovations hold significant potential for advancing medical technologies, particularly in surgery and rehabilitation.
Experience
Hao has participated in several high-profile research projects during his academic career. Notably, he was a major participant in the Rigid-Flexible Coupled Endoscopic Surgical Robot project, which was supported by the National Natural Science Foundation of China. In this project, he worked on developing methods for shape and force sensing in medical continuum robots. Hao’s research has also contributed to the development of flexible sensors and control algorithms for soft robots, including the Ultrasensitive Sensing for Biological Gas-Liquid-Electrical Signals project. His diverse experience in robotics research has led to significant advancements in control technologies and sensory systems.
Research Timeline
Hao’s research timeline began with his Bachelor’s degree in Machine Design, Manufacture, and Automation at Tianjin University from 2016 to 2020. Following this, he pursued his Master’s and Doctoral studies, with his research primarily focused on continuum and soft robots. From 2020 onward, Hao’s work has centered around advanced control algorithms, shape and force estimation, and adaptive systems for medical robots. His involvement in key projects, such as the endoscopic surgical robot and flexible surgical instruments, has been pivotal in developing practical solutions for real-world applications in robotics.
Awards & Honors
Hao has received numerous accolades for his research contributions. Notably, he was recognized on the cover issue of Advanced Intelligent Systems in 2023 for his work on soft robotics shape estimation. He has also been acknowledged as the first author in prestigious journals like IEEE Transactions on Medical Robotics and Bionics and IEEE Sensors Journal. Additionally, Hao has earned multiple merit-based scholarships and awards for his academic excellence, further cementing his reputation as a promising researcher in the field of robotics.
Top-Noted Publications
- Curvature Estimation of Soft Grippers Based on a Novel Highly Stretchable Strain Sensor With Worm-Surface-Like Microstructures
- Authors: Yan, L., Hao, J., Zhang, Z., Yang, H., Shi, C.
- Journal: IEEE Sensors Journal, 2024, 24(4), pp. 4246–4257
- Citations: 1
- Desmoking of the Endoscopic Surgery Images Based on A Local-Global U-Shaped Transformer Model
- Authors: Wang, W., Liu, F., Hao, J., Zhang, B., Shi, C.
- Journal: IEEE Transactions on Medical Robotics and Bionics, 2024 (Article in Press)
- Citations: 0
- An Occlusion Removal Approach for Surgical Instruments Based on the Optical Flow-Guided Models
- Authors: Wang, W., Liu, F., Hao, J., Shi, C.
- Conference: 2024 IEEE International Conference on Mechatronics and Automation, ICMA 2024, pp. 1532–1537
- Citations: 0
- An Operating Stiffness Controller for the Medical Continuum Robot Based on Impedance Control
- Authors: Duan, J., Zhang, K., Qian, K., Hao, J., Zhang, Z., Shi, C.
- Journal: Cyborg and Bionic Systems, 2024, 5, 0110
- Citations: 4
- Inverse Kinematic Modeling of the Tendon-Actuated Medical Continuum Manipulator Based on a Lightweight Timing Input Neural Network
- Authors: Hao, J., Duan, J., Wang, K., Hu, C., Shi, C.
- Journal: IEEE Transactions on Medical Robotics and Bionics, 2023, 5(4), pp. 916–928
- Citations: 6