Reduced Dynamics and Control for an Autonomous Bicycle

Xiong, Jingang; Li, Bo; Yu, Ruihan; Ma, Dongli; Wang, Wei; Liu, Caishan

doi:10.1109/icra48506.2021.9560905

Cited by 6 publications

(2 citation statements)

References 22 publications

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“…We specify the control law as follows: the steer angle is a linear function of the lean angle with fixed slope and intercept, and the angular velocity of the rear wheel is constant. Basically, this control law is a natural extension of the proportional control law proposed in our previous work [75].…”

Section: Contributions and Organizationsmentioning

confidence: 96%

Steering Control and Stability Analysis for an Autonomous Bicycle through Reduced Dynamics with Servo-Constraints

Liu

xiong

2022

Preprint

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Stability of rider-controlled bicycles is related to the appropriate coupling between leaning and steering. Inspired by this driving experience, we propose a linear control law between steer and lean angles to balance motion of an unmanned bicycle. The selection of the control parameters is based on stability analysis for the controlled bicycle dynamics, in which the control law and the constant rear-wheel velocity ω0 serve as servo-constraints imposed to the bicycle system. To facilitate the stability analysis of the controlled motion, we use tools from geometric mechanics to reduce the bicycle's dynamics, leading to a two-dimensional dynamic system. We thereafter study its relative equilibria and related stability. Theoretical results show that there is a critical value of ωc, above which the bicycle can move in a stable uniform straight forward motion, and below which a pair of relative equilibria related to stable uniform circular motion exist. The driving rule of steering toward a fall (STF) and counter-steering (CST) can also be explained theoretically. Finally, we fabricate a powered autonomous bicycle and propose an error correction algorithm to eliminate the drift error of the gyroscope sensor. Our experimental results are in good agreement with the theoretical predictions. Generally, this paper presents the mathematical basis for designing the more advanced and intelligent autonomous bicycles, and may find potential applications in other vehicle systems.

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Section: Contributions and Organizationsmentioning

confidence: 96%

Steering Control and Stability Analysis for an Autonomous Bicycle through Reduced Dynamics with Servo-Constraints

Liu

xiong

2022

Preprint

Self Cite

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“…Automated driving technology is a widely concerned issue today, with safe driving being a major concern for the public [1]. The trajectory of the wheels is an important focus in the study of safe vehicle driving.…”

Section: Introductionmentioning

confidence: 99%

Bicycle Trajectory Control Based on Kinematic and Dynamical Models

2023

AJMS

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This paper uses a bicycle model as an example to explore its travel pattern and corresponding trajectory. The movement of the bicycle changes depends on the road conditions. The kinematic and dynamical models are used to explore its movement patterns in low and high speed states. A simplified version of the bicycle trajectory is obtained by controlling the deflection angle and the total body length. It is found that the front and rear wheel trajectories are concentric circles with the same point as the centre and different radii, and the position of the centre of mass affects the central trajectory. The model is applied to trajectory mapping to make a Taiji diagram.

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The equivalence of Boltzmann–Hamel and Gibbs–Appell equations in modeling constrained systems

Pius

Selekwa

2023

Int. J. Dynam. Control

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Reduced Dynamics and Control for an Autonomous Bicycle

Cited by 6 publications

References 22 publications

Steering Control and Stability Analysis for an Autonomous Bicycle through Reduced Dynamics with Servo-Constraints

Steering Control and Stability Analysis for an Autonomous Bicycle through Reduced Dynamics with Servo-Constraints

Bicycle Trajectory Control Based on Kinematic and Dynamical Models

The equivalence of Boltzmann–Hamel and Gibbs–Appell equations in modeling constrained systems

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