Trajectory Planning for Mobile Robots with Considering Velocity Constraints on Xenomai

Yang, Gil Jin; Choi, Byoung Wook

doi:10.14257/astl.2014.49.01

Cited by 9 publications

(32 citation statements)

References 4 publications

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“…In path planning of a mobile robot, the initial and terminal position with their corresponding heading angles should all be considered. A cubic Bezier curve is generated from an initial point P(A 0 , B 0 ), end point S(A 3 , B 3 ), and two control points that represented by Q(A 1 , B 1 ) and R(A 2 , B 2 ) as found in [1].…”

Section: Figure 1 Kinematics Of a Mobile Robotmentioning

confidence: 99%

“…The central velocity generated using the convolution operator does not consider the angular disposition of the mobile robot [1]. Thus, in order to determine its position while travelling along a Bezier curve, the parameter u(t) is calculated using (7):…”

Section: Figure 3 Central Velocity Based On Convolutionmentioning

confidence: 99%

“…Different approaches were made for the path planning that involves different types of curves such as cubic splines [2], cubic spirals [3], and Bezier curves [1,[4][5]. Another crucial factor to be considered during path planning is satisfying the physical constraints of a mobile robot.…”

Section: Introductionmentioning

confidence: 99%

“…Any violation to these limitations would make the robot vulnerable to potential damage and produce inaccurate trajectory. Thus, various researches were made in order to deal with these limits such as the maximum velocity, maximum acceleration, and maximum jerk [1,[3][4]6].…”

Section: Introductionmentioning

confidence: 99%

“…Even though the central velocity of the robot generated using a convolution operator [10] is able to compromise the physical limits of the mobile robot, it did not consider the direction angle for a Bezier path because the convolution-based method only considers the linear distance between two points. In [1], a path planning algorithm was suggested to consider the direction angle. The modified velocity shows high accuracy in meeting the required terminal velocity however, the trajectory could not follow a planned path with high curvature.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Convolution-based Time Optimal Path Planning for a High Curvature Bezier Curve Considering Possible Physical Limits

Yang¹,

Delagado²,

Choi³

2015

IJCA

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Section: Figure 1 Kinematics Of a Mobile Robotmentioning

confidence: 99%

Section: Figure 3 Central Velocity Based On Convolutionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Convolution-based Time Optimal Path Planning for a High Curvature Bezier Curve Considering Possible Physical Limits

Yang¹,

Delagado²,

Choi³

2015

IJCA

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Practical high curvature path planning algorithm in joint space

Delgado

Choi

2015

Electron. lett.

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A practical high curvature path planning algorithm that considers the velocity limit of a mobile robot in joint space is proposed. The existence of obstacles that constrict the smooth movement of mobile robots is inevitable. To avoid incoming collision, the robot is redirected to a new path with respect to the dimensions of the obstacle and a safety factor. The redirected path consists of geometric constraints such as high curvatures on its turning points which cause difficulty in controlling the mobile robot. Thus, a central velocity generation method that considers both velocity limits through a convolution operator and high curvatures at turning points is suggested. The central velocity is able to be within the configured velocity limit, otherwise actual velocity commands in joint space could result. Therefore, interpolation to obtain uniform sampling and velocity downscaling is performed to generate a feasible joint space trajectory. The result shows short travelling time compared with previous methods while satisfying velocity limits in the joint space.

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Gait planning and control of quadruped crawling robot on a slope

Wang

Song

et al. 2019

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Purpose The gait planning and control of quadruped crawling robot affect the stability of the robot walking on a slope. The control includes the position control in the swing phase, the force control in the support phase and the switching control in the force/position switching. To improve the passing ability of quadruped crawling robot on a slope, this paper aims to propose a soft control strategy. Design/methodology/approach The strategy adopts the statically stable crawling gait as the main gait. As the robot moves forward, the position/force section switching control is adopted. When the foot does not touch the ground, the joint position control based on the variable speed PID is performed. When the foot touches the ground, the position-based impedance control is performed, and a fuzzy multi-model switching control based on friction compensation is proposed to achieve smooth switching of force and position. Findings The proposed method offers a solution for stable passage in slope environment. The quadruped crawling robot can realize smooth switching of force/position, precise positioning in the swing process and soft control of force in the supporting phase. This fact is verified by simulation and test. Originality/value The method presented in this paper takes advantage of minimal tracking errors and minimal jitters. Simulations and tests were performed to evaluate the performance.

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Trajectory Planning for Mobile Robots with Considering Velocity Constraints on Xenomai

Cited by 9 publications

References 4 publications

Convolution-based Time Optimal Path Planning for a High Curvature Bezier Curve Considering Possible Physical Limits

Convolution-based Time Optimal Path Planning for a High Curvature Bezier Curve Considering Possible Physical Limits

Practical high curvature path planning algorithm in joint space

Gait planning and control of quadruped crawling robot on a slope

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