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Zhao M, Hu B. Special Issue: Design and Control of a Bio-Inspired Robot. Biomimetics (Basel) 2024; 9:43. [PMID: 38248617 PMCID: PMC10813440 DOI: 10.3390/biomimetics9010043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 01/09/2024] [Indexed: 01/23/2024] Open
Abstract
Bionics, the interdisciplinary field that draws inspiration from nature to design and develop innovative technologies, has paved the way for the creation of "bio-inspired robots" [...].
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Affiliation(s)
- Mingguo Zhao
- Department of Automation, Tsinghua University, Beijing 100084, China;
| | - Biao Hu
- College of Engineering, China Agricultural University, Beijing 100083, China
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Wang Q, Wei B, Wei Z, Gao S, Jin X, Yang P. Reconstruction of a Car-Running Pedestrian Accident Based on a Humanoid Robot Method. SENSORS (BASEL, SWITZERLAND) 2023; 23:7882. [PMID: 37765938 PMCID: PMC10535210 DOI: 10.3390/s23187882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 09/06/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023]
Abstract
Due to the characteristics of multibody (MB) and finite element (FE) digital human body models (HBMs), the reconstruction of running pedestrians (RPs) remains a major challenge in traffic accidents (TAs) and new innovative methods are needed. This study presents a novel approach for reconstructing moving pedestrian TAs based on a humanoid robot method to improve the accuracy of analyzing dynamic vehicle-pedestrian collision accidents. Firstly, we applied the theory of humanoid robots to the corresponding joints and centroids of the TNO HBM and implemented the pedestrian running process. Secondly, we used rigid-flexible coupling HBMs to build pedestrians, which can not only simulate running but also analyze human injuries. Then, we validated the feasibility of the RP reconstruction method by comparing the simulated dynamics with the pedestrian in the accident. Next, we extracted the velocity and posture of the pedestrian at the moment of collision and further validated the modeling method through a comparison of human injuries and forensic autopsy results. Finally, by comparing two other cases, we can conclude that there are relative errors in both the pedestrian injury results and the rest position. This comparative analysis is helpful for understanding the differences in injury characteristics between the running pedestrian and the other two cases in TAs.
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Affiliation(s)
- Qian Wang
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Bo Wei
- Aerospace System Engineering Shanghai, Shanghai 201109, China
| | - Zheng Wei
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Shang Gao
- School of Petroleum Engineering, China University of Petroleum, Qingdao 266580, China
| | - Xianlong Jin
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Peizhong Yang
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
- State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China
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Li Y, Chen Z, Wu C, Mao H, Sun P. A Hierarchical Framework for Quadruped Robots Gait Planning Based on DDPG. Biomimetics (Basel) 2023; 8:382. [PMID: 37754133 PMCID: PMC10526411 DOI: 10.3390/biomimetics8050382] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 08/16/2023] [Accepted: 08/18/2023] [Indexed: 09/28/2023] Open
Abstract
In recent years, significant progress has been made in employing reinforcement learning for controlling legged robots. However, a major challenge arises with quadruped robots due to their continuous states and vast action space, making optimal control using simple reinforcement learning controllers particularly challenging. This paper introduces a hierarchical reinforcement learning framework based on the Deep Deterministic Policy Gradient (DDPG) algorithm to achieve optimal motion control for quadruped robots. The framework consists of a high-level planner responsible for generating ideal motion parameters, a low-level controller using model predictive control (MPC), and a trajectory generator. The agents within the high-level planner are trained to provide the ideal motion parameters for the low-level controller. The low-level controller uses MPC and PD controllers to generate the foot-end force and calculates the joint motor torque through inverse kinematics. The simulation results show that the motion performance of the trained hierarchical framework is superior to that obtained using only the DDPG method.
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Affiliation(s)
- Yanbiao Li
- College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China; (Y.L.); (Z.C.); (C.W.); (H.M.)
- Key Laboratory of Special Purpose Equipment and Advanced Processing Technology, Ministry of Education and Zhejiang Province, Zhejiang University of Technology, Hangzhou 310023, China
| | - Zhao Chen
- College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China; (Y.L.); (Z.C.); (C.W.); (H.M.)
- Key Laboratory of Special Purpose Equipment and Advanced Processing Technology, Ministry of Education and Zhejiang Province, Zhejiang University of Technology, Hangzhou 310023, China
- Huzhou Institute of Digital Economy and Technology, Zhejiang University of Technology, Huzhou 313000, China
| | - Chentao Wu
- College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China; (Y.L.); (Z.C.); (C.W.); (H.M.)
- Key Laboratory of Special Purpose Equipment and Advanced Processing Technology, Ministry of Education and Zhejiang Province, Zhejiang University of Technology, Hangzhou 310023, China
| | - Haoyu Mao
- College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China; (Y.L.); (Z.C.); (C.W.); (H.M.)
- Key Laboratory of Special Purpose Equipment and Advanced Processing Technology, Ministry of Education and Zhejiang Province, Zhejiang University of Technology, Hangzhou 310023, China
- Huzhou Institute of Digital Economy and Technology, Zhejiang University of Technology, Huzhou 313000, China
| | - Peng Sun
- College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China; (Y.L.); (Z.C.); (C.W.); (H.M.)
- Key Laboratory of Special Purpose Equipment and Advanced Processing Technology, Ministry of Education and Zhejiang Province, Zhejiang University of Technology, Hangzhou 310023, China
- Huzhou Institute of Digital Economy and Technology, Zhejiang University of Technology, Huzhou 313000, China
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