3-dimensional kinodynamic motion planning for an X4-Flyer using 2-dimensional harmonic potential fields

Motonaka, Kimiko; Watanabe, Keigo; Maeyama, Shoichi

doi:10.1109/iccas.2014.6987738

Cited by 8 publications

(3 citation statements)

References 6 publications

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“…Motonaka et al using kinodynamic motion planning approach performed simulations to guide a quadcopter (X4-Flyer) utilizing a harmonic potential field in three-dimensional space [4].…”

Section: Introductionmentioning

confidence: 99%

Trajectory generation with piecewise constant acceleration and tracking control of a quadcopter

Jang

Moon

Han

et al. 2015

2015 IEEE International Conference on Industrial Technology (ICIT)

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This paper describes a 3D reference trajectory generation and tracking control method for a quadcopter. The flying trajectory is a piecewise curve that passes through viapoints at specified times or speeds and has constant acceleration within each interval. The path is first represented as the third degree polynomials, and to overcome demerits of the C-splines, a numeric algorithm is suggested and implemented. The feasibility of the generated trajectory is checked by nonlinear dynamics model of a quadcopter. After executing several flying experiments for a quadcopter, tracking errors are evaluated.

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“…Motonaka et al using kinodynamic motion planning approach performed simulations to guide a quadcopter (X4-Flyer) utilizing a harmonic potential field in three-dimensional space [4].…”

Section: Introductionmentioning

confidence: 99%

Trajectory generation with piecewise constant acceleration and tracking control of a quadcopter

Jang

Moon

Han

et al. 2015

2015 IEEE International Conference on Industrial Technology (ICIT)

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“…Traditional path planning includes methods based on virtual potential field or heuristic rules and methods based on mathematical optimization. The former methods are widely used in 2D path planning, especially the harmonic potential field method [ 21 , 22 ] and artificial potential field method [ 18 , 23 ], which have been successfully extended to 3D space. Methods based on mathematical optimization mainly contain the nonlinear classification method of the support vector machine [ 24 ], linear programming method, mixed integer linear programming method [ 25 ], etc.…”

Section: Introductionmentioning

confidence: 99%

3D Path Planning for the Ground Robot with Improved Ant Colony Optimization

Wang

Kan

Guo

et al. 2019

Sensors

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Path planning is a fundamental issue in the aspect of robot navigation. As robots work in 3D environments, it is meaningful to study 3D path planning. To solve general problems of easily falling into local optimum and long search times in 3D path planning based on the ant colony algorithm, we proposed an improved the pheromone update and a heuristic function by introducing a safety value. We also designed two methods to calculate safety values. Concerning the path search, we designed a search mode combining the plane and visual fields and limited the search range of the robot. With regard to the deadlock problem, we adopted a 3D deadlock-free mechanism to enable ants to get out of the predicaments. With respect to simulations, we used a number of 3D terrains to carry out simulations and set different starting and end points in each terrain under the same external settings. According to the results of the improved ant colony algorithm and the basic ant colony algorithm, paths planned by the improved ant colony algorithm can effectively avoid obstacles, and their trajectories are smoother than that of the basic ant colony algorithm. The shortest path length is reduced by 8.164%, on average, compared with the results of the basic ant colony algorithm. We also compared the results of two methods for calculating safety values under the same terrain and external settings. Results show that by calculating the safety value in the environmental modeling stage in advance, and invoking the safety value directly in the path planning stage, the average running time is reduced by 91.56%, compared with calculating the safety value while path planning.

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“…Moreover, they offer a complete path planning algorithm, and paths derived from them are generally smooth. In the past, an exact method based on the HPFs were applied in many area of researches including ship navigation [5], trajectory control [6], space robot path planning [7], navigation of snake-like robot [8], UAV motion planning [9], marine vessel path planning [10], 3D motion planning for UAV [11,12], space exploration [13], etc. In robot navigation problem, the HPFs were successfully applied in various types of environments [14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Path Planning in Structured Environment using Harmonic Potential Fields via Block Iterative Method

2017

CAFES-17, ICFCT-2017, SDMCAE-17 April 18-19, 2017 Kyoto (Japan)

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3-dimensional kinodynamic motion planning for an X4-Flyer using 2-dimensional harmonic potential fields

Cited by 8 publications

References 6 publications

Trajectory generation with piecewise constant acceleration and tracking control of a quadcopter

Trajectory generation with piecewise constant acceleration and tracking control of a quadcopter

3D Path Planning for the Ground Robot with Improved Ant Colony Optimization

Path Planning in Structured Environment using Harmonic Potential Fields via Block Iterative Method

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