Real-time quintic Hermite interpolation for robot trajectory execution

Lind, Morten

doi:10.7717/peerj-cs.304

Cited by 4 publications

(2 citation statements)

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“…According to the relevant theory of the Hermitian curve [25], the two-point cubic Hermitian curve is determined by four quantities: the starting point A, the starting point tangent K a , the ending point B, and the ending point tangent K b . When the node moves, the vector velocity of the node is equal to the tangent line, so let K a = V i , K b = V i+1 , According to the nature of the Hermite curve, the curvature of the curve can be changed by changing V i+1 the starting point P i of the curve.…”

Section: Model Definitionmentioning

confidence: 99%

A novel mobility model adapted to multi-obstacle scenarios: obstacle avoidance and smooth motion

Shi

Wang

Zhang

2023

Preprint

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Most of the existing mobility models use simple, linear motion to describe node movement, and there are few studies on curve movement patterns based on multiple obstacles in real scenes. How to describe the avoidance and curve movement patterns of nodes in multivariate obstacle scenes has become a key difficulty in mobility modeling. To address this, this paper proposes a mobility model based on Hermite curves, which fills the gap in curve mobility models for complex, multivariate obstacle scenes in mobility modeling. Firstly, the paper analyzes the demands of mobile patterns in real scenes, and then theoretically models the Hermite curve direction, combining node movement with Hermite curves to achieve curve movement, and adding perception parameters to avoid obstacles. To study the model's performance in practical scenes, this paper researches the spatial probability distribution of nodes and the spatio-temporal dynamic characteristics of network topology under the model's action, and defines the evaluation indicators of the model. To demonstrate the model's application performance, it is compared with the curve mobility model SRMM and the classic RWPM model. The results show that the model not only adapts to the obstacle avoidance application scenes with multiple obstacles, but also has a more uniform spatial probability distribution of nodes, better spatial coverage, and better spatio-temporal dynamic characteristics of the network topology composed of nodes than the SRMM and RWPM models. This model can provide a more realistic application scenes for the simulation of MANET.

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Section: Model Definitionmentioning

confidence: 99%

A novel mobility model adapted to multi-obstacle scenarios: obstacle avoidance and smooth motion

Shi

Wang

Zhang

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…where n is the degree of the interpolation, p (i) 0 (p (i) 1 ) is the i-th derivative at t 0 (t 1 ) and u is the normalized time variable ((t − t 0 )/(t 1 − t 0 )). The polynomials H n i are given by the line of the following matrix where the first column corresponds to the constant term (Lind 2020):…”

Section: Appendix a Interpolation With Co-moving Coordinatesmentioning

confidence: 99%