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Trajectory Deformation Through Generalized Time Scaling

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Trajectory Deformation Through Generalized Time Scaling. / Singh, Arun Kumar; Ghabcheloo, Reza.

2018 European Control Conference (ECC). IEEE, 2018. s. 614-621.

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Harvard

Singh, AK & Ghabcheloo, R 2018, Trajectory Deformation Through Generalized Time Scaling. julkaisussa 2018 European Control Conference (ECC). IEEE, Sivut 614-621, European Control Conference, 1/01/00. https://doi.org/10.23919/ECC.2018.8550056

APA

Singh, A. K., & Ghabcheloo, R. (2018). Trajectory Deformation Through Generalized Time Scaling. teoksessa 2018 European Control Conference (ECC) (Sivut 614-621). IEEE. https://doi.org/10.23919/ECC.2018.8550056

Vancouver

Singh AK, Ghabcheloo R. Trajectory Deformation Through Generalized Time Scaling. julkaisussa 2018 European Control Conference (ECC). IEEE. 2018. s. 614-621 https://doi.org/10.23919/ECC.2018.8550056

Author

Singh, Arun Kumar ; Ghabcheloo, Reza. / Trajectory Deformation Through Generalized Time Scaling. 2018 European Control Conference (ECC). IEEE, 2018. Sivut 614-621

Bibtex - Lataa

@inproceedings{da6c93c141d74ce4b651ecde292cbdc5,
title = "Trajectory Deformation Through Generalized Time Scaling",
abstract = "In this paper, we propose a new concept called Generalized Time Scaling (GTS) which as the name suggests is a generalization of the time scaling concept extensively used for the kino-dynamic motion planning of robots. Given a trajectory, a time scaling transformation modifies the motion profile of the trajectory while preserving the geometric path associated with it. In contrast, GTS transformation modifies both the motion profile as well as the geometric path of the given trajectory. We show that this feature of GTS can be leveraged to derive a new formulation for trajectory deformation which in turn has several key advantages over existing frameworks. Firstly, it directly works at the trajectory description level and does not require multiple reintegration of state space models. Secondly, it can can directly deform straight line and circular trajectories into complex shapes. Finally, the proposed formulation takes the form of an optimization problem which is interesting in itself and has potential beyond the proposed work. In particular, we use Augmented Lagrangian (AL) and Alternating Minimization (AM) to reformulate a complex non-convex problem into a sequence of distributed convex optimization problems. As an application, we use the trajectory deformation for the terminal heading correction, goal point correction, collision avoidance of non-holonomic mobile robots as well as for smoothing of trajectories consisting of piece-wise linear and circular segments.",
keywords = "collision avoidance, convex programming, geometry, mobile robots, piecewise linear techniques, trajectory control, trajectory deformation, geometric path, GTS transformation, generalized time scaling, augmented lagrangian, alternating minimization, non-convex problem, convex optimization problems, heading correction, goal point correction, non-holonomic mobile robots, piece-wise linear segments, circular segments, kino-dynamic motion planning, Trajectory, Strain, Robots, Optimization, Minimization, Collision avoidance, Acceleration",
author = "Singh, {Arun Kumar} and Reza Ghabcheloo",
year = "2018",
month = "6",
doi = "10.23919/ECC.2018.8550056",
language = "English",
isbn = "978-1-5386-5303-6",
pages = "614--621",
booktitle = "2018 European Control Conference (ECC)",
publisher = "IEEE",

}

RIS (suitable for import to EndNote) - Lataa

TY - GEN

T1 - Trajectory Deformation Through Generalized Time Scaling

AU - Singh, Arun Kumar

AU - Ghabcheloo, Reza

PY - 2018/6

Y1 - 2018/6

N2 - In this paper, we propose a new concept called Generalized Time Scaling (GTS) which as the name suggests is a generalization of the time scaling concept extensively used for the kino-dynamic motion planning of robots. Given a trajectory, a time scaling transformation modifies the motion profile of the trajectory while preserving the geometric path associated with it. In contrast, GTS transformation modifies both the motion profile as well as the geometric path of the given trajectory. We show that this feature of GTS can be leveraged to derive a new formulation for trajectory deformation which in turn has several key advantages over existing frameworks. Firstly, it directly works at the trajectory description level and does not require multiple reintegration of state space models. Secondly, it can can directly deform straight line and circular trajectories into complex shapes. Finally, the proposed formulation takes the form of an optimization problem which is interesting in itself and has potential beyond the proposed work. In particular, we use Augmented Lagrangian (AL) and Alternating Minimization (AM) to reformulate a complex non-convex problem into a sequence of distributed convex optimization problems. As an application, we use the trajectory deformation for the terminal heading correction, goal point correction, collision avoidance of non-holonomic mobile robots as well as for smoothing of trajectories consisting of piece-wise linear and circular segments.

AB - In this paper, we propose a new concept called Generalized Time Scaling (GTS) which as the name suggests is a generalization of the time scaling concept extensively used for the kino-dynamic motion planning of robots. Given a trajectory, a time scaling transformation modifies the motion profile of the trajectory while preserving the geometric path associated with it. In contrast, GTS transformation modifies both the motion profile as well as the geometric path of the given trajectory. We show that this feature of GTS can be leveraged to derive a new formulation for trajectory deformation which in turn has several key advantages over existing frameworks. Firstly, it directly works at the trajectory description level and does not require multiple reintegration of state space models. Secondly, it can can directly deform straight line and circular trajectories into complex shapes. Finally, the proposed formulation takes the form of an optimization problem which is interesting in itself and has potential beyond the proposed work. In particular, we use Augmented Lagrangian (AL) and Alternating Minimization (AM) to reformulate a complex non-convex problem into a sequence of distributed convex optimization problems. As an application, we use the trajectory deformation for the terminal heading correction, goal point correction, collision avoidance of non-holonomic mobile robots as well as for smoothing of trajectories consisting of piece-wise linear and circular segments.

KW - collision avoidance

KW - convex programming

KW - geometry

KW - mobile robots

KW - piecewise linear techniques

KW - trajectory control

KW - trajectory deformation

KW - geometric path

KW - GTS transformation

KW - generalized time scaling

KW - augmented lagrangian

KW - alternating minimization

KW - non-convex problem

KW - convex optimization problems

KW - heading correction

KW - goal point correction

KW - non-holonomic mobile robots

KW - piece-wise linear segments

KW - circular segments

KW - kino-dynamic motion planning

KW - Trajectory

KW - Strain

KW - Robots

KW - Optimization

KW - Minimization

KW - Collision avoidance

KW - Acceleration

U2 - 10.23919/ECC.2018.8550056

DO - 10.23919/ECC.2018.8550056

M3 - Conference contribution

SN - 978-1-5386-5303-6

SP - 614

EP - 621

BT - 2018 European Control Conference (ECC)

PB - IEEE

ER -