Design and Analysis of the Rolling and Jumping Compound Motion Robot

Wu, Huaisong; Li, Bingyang; Wang, Futao; Luo, Bei; Jiao, Zhiwei; Yu, Yi; Wang, Pengfei

doi:10.3390/app112210667

Cited by 4 publications

(2 citation statements)

References 12 publications

(19 reference statements)

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“…𝑟𝑒𝑤𝑎𝑟𝑑1 1 𝑡𝑎𝑛ℎ 10 |𝑒 | 𝑟𝑒𝑤𝑎𝑟𝑑2 1 𝑡𝑎𝑛ℎ 10 |𝑒 | 𝑟𝑒𝑤𝑎𝑟𝑑 0.5 𝑟𝑒𝑤𝑎𝑟𝑑1 0.5 𝑟𝑒𝑤𝑎𝑟𝑑2 (10) Due to the utilization of the tanh function, the velocity errors are difficult to reduce after it is below a threshold. Switching control is introduced into our controller to obtain smaller errors further.…”

Section: Adaptive Pid Controller Based On Reinforcement Learningmentioning

confidence: 99%

“…Consequently, they have attracted many researchers and have been widely used in the detection of unknown environments [2], environmental monitoring [3,4], surveillance [5], and other fields [6]. Based on the single-motion mode [7][8][9], researchers have gradually developed spherical robots with multi-motion modes, such as rolling and jumping, rolling and crawling, and others [10][11][12][13]. The multi-motion mode further expands the application of spherical robots in environmental detection tasks.…”

Section: Introductionmentioning

confidence: 99%

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Velocity Control of a Multi-Motion Mode Spherical Probe Robot Based on Reinforcement Learning

Cao³

et al. 2023

Applied Sciences

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As deep space exploration tasks become increasingly complex, the mobility and adaptability of traditional wheeled or tracked probe robots with high functional density are constrained in harsh, dangerous, or unknown environments. A practical solution to these challenges is designing a probe robot for preliminary exploration in unknown areas, which is characterized by robust adaptability, simple structure, light weight, and minimal volume. Compared to the traditional deep space probe robot, the spherical robot with a geometric, symmetrical structure shows better adaptability to the complex ground environment. Considering the uncertain detection environment, the spherical robot should brake rapidly after jumping to avoid reentering obstacles. Moreover, since it is equipped with optical modules for deep space exploration missions, the spherical robot must maintain motion stability during the rolling process to ensure the quality of photos and videos captured. However, due to the nonlinear coupling and parameter uncertainty of the spherical robot, it is tedious to adjust controller parameters. Moreover, the adaptability of controllers with fixed parameters is limited. This paper proposes an adaptive proportion–integration–differentiation (PID) control method based on reinforcement learning for the multi-motion mode spherical probe robot (MMSPR) with rolling and jumping. This method uses the soft actor–critic (SAC) algorithm to adjust the parameters of the PID controller and introduces a switching control strategy to reduce static error. As the simulation results show, this method can facilitate the MMSPR’s convergence within 0.02 s regarding motion stability. In addition, in terms of braking, it enables an MMSPR with random initial speed brake within a convergence time of 0.045 s and a displacement of 0.0013 m. Compared with the PID method with fixed parameters, the braking displacement of the MMSPR is reduced by about 38%, and the convergence time is reduced by about 20%, showing better universality and adaptability.

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Section: Adaptive Pid Controller Based On Reinforcement Learningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Velocity Control of a Multi-Motion Mode Spherical Probe Robot Based on Reinforcement Learning

Cao³

et al. 2023

Applied Sciences

Self Cite

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Attitude Control of Multi-motion Mode Spherical Probe Robots Based on Decoupled Dynamics

Chang

Cao³

et al. 2023

Lecture Notes in Electrical Engineering

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System design and control of the sphere-wheel-legged robot

Liang,

Xu,

Han

et al. 2024

Robotica

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The two-wheeled legged robot combines the advantages of legged robot and wheeled robot and has high terrain adaptability. Spherical robots are highly resistant to interference during detection. In this paper, a new sphere-wheel-legged robot is designed by combining these three motion modes. This paper begins by introducing the mechanical design, hardware, and software. Then, kinematics and dynamics of wheel-legged motion and spherical motion are analyzed in detail. Subsequently, the controllers for wheel-legged balancing motion, wheel-legged jumping motion, and sphere rolling motion are developed, respectively. Finally, experiments are carried out for different modes. The results demonstrate that the designed robot has excellent locomotor capabilities over different terrains.

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Design and Analysis of the Rolling and Jumping Compound Motion Robot

Cited by 4 publications

References 12 publications

Velocity Control of a Multi-Motion Mode Spherical Probe Robot Based on Reinforcement Learning

Velocity Control of a Multi-Motion Mode Spherical Probe Robot Based on Reinforcement Learning

Attitude Control of Multi-motion Mode Spherical Probe Robots Based on Decoupled Dynamics

System design and control of the sphere-wheel-legged robot

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