Research Status on Jumping Function of Quadruped Robots
The jumping function of quadruped robots is an important ability to achieve high maneuverability and adaptability in complex environments. The current research status of the jumping function of quadruped robots was reviewed, including the latest progress in the structural design, the control model d...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Transmission
2024-01-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails?columnId=67583668&Fpath=home&index=0 |
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| _version_ | 1841546951662764032 |
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| author | Hua Congcong Yang Zihe Xia Yanting Yan Jianrong Gao Guanjian Luo Fuliang Ma Wenshuo Li Zhijie |
| author_facet | Hua Congcong Yang Zihe Xia Yanting Yan Jianrong Gao Guanjian Luo Fuliang Ma Wenshuo Li Zhijie |
| author_sort | Hua Congcong |
| collection | DOAJ |
| description | The jumping function of quadruped robots is an important ability to achieve high maneuverability and adaptability in complex environments. The current research status of the jumping function of quadruped robots was reviewed, including the latest progress in the structural design, the control model design, and the control algorithm design. In terms of the structural design based on the jumping function, the skeleton structure, joint design, and material selection of quadruped robots were optimized to improve the jumping ability and the stability. In the design of control models based on the jumping function, various dynamic models were proposed to describe the jumping behavior of quadruped robots. These models can be used to predict and optimize the jump performance, and provide a foundation for the subsequent control algorithm design. An accurate control model can ensure the stable and precise control, thereby improving the jumping performance and adaptability of robots. In the design of control algorithms based on the jump function, traditional control methods such as PID control, fuzzy control, and adaptive control were widely used in the control of jump function. In addition, advanced control methods such as reinforcement learning, neural networks, and genetic algorithms also were explored and applied. These methods can improve the jumping performance, the stability, and the adaptability, enabling robots to achieve efficient jumping in dynamic and complex environments. |
| format | Article |
| id | doaj-art-9280a65b9b664a4da7a012ba11e79270 |
| institution | Kabale University |
| issn | 1004-2539 |
| language | zho |
| publishDate | 2024-01-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj-art-9280a65b9b664a4da7a012ba11e792702025-01-10T15:01:06ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392024-01-0111367583668Research Status on Jumping Function of Quadruped RobotsHua CongcongYang ZiheXia YantingYan JianrongGao GuanjianLuo FuliangMa WenshuoLi ZhijieThe jumping function of quadruped robots is an important ability to achieve high maneuverability and adaptability in complex environments. The current research status of the jumping function of quadruped robots was reviewed, including the latest progress in the structural design, the control model design, and the control algorithm design. In terms of the structural design based on the jumping function, the skeleton structure, joint design, and material selection of quadruped robots were optimized to improve the jumping ability and the stability. In the design of control models based on the jumping function, various dynamic models were proposed to describe the jumping behavior of quadruped robots. These models can be used to predict and optimize the jump performance, and provide a foundation for the subsequent control algorithm design. An accurate control model can ensure the stable and precise control, thereby improving the jumping performance and adaptability of robots. In the design of control algorithms based on the jump function, traditional control methods such as PID control, fuzzy control, and adaptive control were widely used in the control of jump function. In addition, advanced control methods such as reinforcement learning, neural networks, and genetic algorithms also were explored and applied. These methods can improve the jumping performance, the stability, and the adaptability, enabling robots to achieve efficient jumping in dynamic and complex environments.http://www.jxcd.net.cn/thesisDetails?columnId=67583668&Fpath=home&index=0Quadruped robotJump functionStructure designControl modelControl algorithm |
| spellingShingle | Hua Congcong Yang Zihe Xia Yanting Yan Jianrong Gao Guanjian Luo Fuliang Ma Wenshuo Li Zhijie Research Status on Jumping Function of Quadruped Robots Jixie chuandong Quadruped robot Jump function Structure design Control model Control algorithm |
| title | Research Status on Jumping Function of Quadruped Robots |
| title_full | Research Status on Jumping Function of Quadruped Robots |
| title_fullStr | Research Status on Jumping Function of Quadruped Robots |
| title_full_unstemmed | Research Status on Jumping Function of Quadruped Robots |
| title_short | Research Status on Jumping Function of Quadruped Robots |
| title_sort | research status on jumping function of quadruped robots |
| topic | Quadruped robot Jump function Structure design Control model Control algorithm |
| url | http://www.jxcd.net.cn/thesisDetails?columnId=67583668&Fpath=home&index=0 |
| work_keys_str_mv | AT huacongcong researchstatusonjumpingfunctionofquadrupedrobots AT yangzihe researchstatusonjumpingfunctionofquadrupedrobots AT xiayanting researchstatusonjumpingfunctionofquadrupedrobots AT yanjianrong researchstatusonjumpingfunctionofquadrupedrobots AT gaoguanjian researchstatusonjumpingfunctionofquadrupedrobots AT luofuliang researchstatusonjumpingfunctionofquadrupedrobots AT mawenshuo researchstatusonjumpingfunctionofquadrupedrobots AT lizhijie researchstatusonjumpingfunctionofquadrupedrobots |