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相关论文: Stable Synchronous Propagation in Feedforward Netw…

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We analyse the dynamics of networks in which a central pattern generator (CPG) transmits signals along one or more feedforward chains in a synchronous or phase-synchronous manner. Such propagating signals are common in biology, especially…

动力系统 · 数学 2023-09-08 Ian Stewart , David Wood

Periodic signals propagating along chains are common in biology, for example in locomotion and peristalsis, and are also of interest for continuum robots. In previous work we constructed such networks as 'feedforward lifts' of a central…

混沌动力学 · 物理学 2025-06-16 Ian Stewart , David Wood

Biological studies reveal that neural circuits located at the spinal cord called central pattern generator (CPG) oscillates and generates rhythmic signals, which are the underlying mechanism responsible for rhythmic locomotion behaviors of…

机器人学 · 计算机科学 2023-05-15 Chuanyu Yang , Can Pu , Tianqi Wei , Cong Wang , Zhibin Li

Central pattern generators (CPGs), with a basis is neurophysiological studies, are a type of neural network for the generation of rhythmic motion. While CPGs are being increasingly used in robot control, most applications are hand-tuned for…

神经与进化计算 · 计算机科学 2015-03-13 Atilim Gunes Baydin

This paper presents a bio-inspired central pattern generator (CPG)-type architecture for learning optimal maneuvering control of periodic locomotory gaits. The architecture is presented here with the aid of a snake robot model problem…

系统与控制 · 电气工程与系统科学 2019-10-08 Tixian Wang , Amirhossein Taghvaei , Prashant G. Mehta

The gait generator, which is capable of producing rhythmic signals for coordinating multiple joints, is an essential component in the quadruped robot locomotion control framework. The biological counterpart of the gait generator is the…

机器人学 · 计算机科学 2024-06-21 Yide Liu , Xiyan Liu , Dongqi Wang , Wei Yang , shaoxing Qu

Legged locomotion is a challenging task in the field of robotics but a rather simple one in nature. This motivates the use of biological methodologies as solutions to this problem. Central pattern generators are neural networks that are…

神经与进化计算 · 计算机科学 2020-03-18 Elie Aljalbout , Florian Walter , Florian Röhrbein , Alois Knoll

In recent years, locomotion mechanisms exhibited by vertebrate animals have been the inspiration for the improvement in the performance of robotic systems. These mechanisms include the adaptability of their locomotion to any change…

Animals possess a remarkable ability to navigate challenging terrains, achieved through the interplay of various pathways between the brain, central pattern generators (CPGs) in the spinal cord, and musculoskeletal system. Traditional…

机器人学 · 计算机科学 2024-04-30 Ge Sun , Milad Shafiee , Peizhuo Li , Guillaume Bellegarda , Auke Ijspeert , Guillaume Sartoretti

An originally chaotic system can be controlled into various periodic dynamics. When it is implemented into a legged robot's locomotion control as a central pattern generator (CPG), sophisticated gait patterns arise so that the robot can…

We present a model of the central pattern generator (CPG) network that can control gait transitions in hexapod robots in a simple manner based on phase reduction. The CPG network consists of six weakly coupled limit-cycle oscillators, whose…

适应与自组织系统 · 物理学 2025-06-18 Norihisa Namura , Hiroya Nakao

The complexity of bipedal locomotion may be attributed to the difficulty in synchronizing joint movements while at the same time achieving high-level objectives such as walking in a particular direction. Artificial central pattern…

神经与进化计算 · 计算机科学 2019-09-15 Sayantan Auddy , Sven Magg , Stefan Wermter

Stick insect stepping patterns have been studied for insights about locomotor rhythm generation and control, because the underlying neural system is relatively accessible experimentally and produces a variety of rhythmic outputs. Harnessing…

神经元与认知 · 定量生物学 2025-04-17 Zahra Aminzare , Jonathan E. Rubin

Locomotion is a crucial challenge for legged robots that is addressed "effortlessly" by biological networks abundant in nature, named central pattern generators (CPG). The multitude of CPG network models that have so far become biomimetic…

神经与进化计算 · 计算机科学 2020-06-09 Ioannis Polykretis , Konstantinos P. Michmizos

We have been developing human-sized biped robots based on passive dynamic mechanisms. In human locomotion, the muscles activate at the same rate relative to the gait cycle during running. To achieve adaptive running for robots, such…

机器人学 · 计算机科学 2024-03-15 Yusuke Sakurai , Tomoya Kamimura , Yuki Sakamoto , Shohei Nishii , Kodai Sato , Yuta Fujiwara , Akihito Sano

For a robot to be both autonomous and collaborative requires the ability to adapt its movement to a variety of external stimuli, whether these come from humans or other robots. Typically, legged robots have oscillation periods explicitly…

机器人学 · 计算机科学 2023-07-03 Alex Szorkovszky , Frank Veenstra , Kyrre Glette

Inspired by biological motion generation, central pattern generators (CPGs) is frequently employed in legged robot locomotion control to produce natural gait pattern with low-dimensional control signals. However, the limited adaptability…

机器人学 · 计算机科学 2023-10-13 Qiyue Yang , Yue Gao , Shaoyuan Li

All vertebrates are capable of performing various types of physical activity. Locomotor patterns are created by the cyclical coordinated work of the skeletal muscles. The organization of such a system in living organisms is responsible for…

神经元与认知 · 定量生物学 2021-12-15 A. I. Zharinov , Y. A. Tsybina , S. Y. Gordleeva

Quadruped animal locomotion emerges from the interactions between the spinal central pattern generator (CPG), sensory feedback, and supraspinal drive signals from the brain. Computational models of CPGs have been widely used for…

机器人学 · 计算机科学 2023-02-28 Milad Shafiee , Guillaume Bellegarda , Auke Ijspeert

Stability is a fundamental property of dynamical systems, yet to this date it has had little bearing on the practice of recurrent neural networks. In this work, we conduct a thorough investigation of stable recurrent models. Theoretically,…

机器学习 · 计算机科学 2019-03-05 John Miller , Moritz Hardt
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