scholarly journals Topological complexity of collision free motion planning algorithms in the presence of multiple moving obstacles

2007 ◽  
pp. 75-83 ◽  
Author(s):  
Michael Farber ◽  
Mark Grant ◽  
Sergey Yuzvinsky
Keyword(s):  
Motion Planning ◽  
Free Motion ◽  
Topological Complexity ◽  
Moving Obstacles ◽  
Planning Algorithms

scholarly journals Uncertain estimation-based motion-planning algorithms for mobile robots

ACTA IMEKO ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 51
Author(s):  
Zoltán Bálint Gyenes ◽  
Emese Gincsainé Szádeczky-Kardoss
Keyword(s):  
Motion Planning ◽  
Mobile Agents ◽  
Dynamic Environment ◽  
Target Position ◽  
Free Motion ◽  
Artificial Potential Field ◽  
Moving Obstacles ◽  
Other Information ◽  
Planning Algorithms ◽  
Velocity Obstacle

Collision-free motion planning for mobile agents is a challenging task, especially when the robot has to move towards a target position in a dynamic environment. The main aim of this paper is to introduce motion-planning algorithms using the changing uncertainties of the sensor-based data of obstacles. Two main algorithms are presented in this work. The first is based on the well-known velocity obstacle motion-planning method. In this method, collision-free motion must be achieved by the algorithm using a cost-function-based optimisation method. The second algorithm is an extension of the often-used artificial potential field. For this study, it is assumed that some of the obstacle data (e.g. the positions of static obstacles) are already known at the beginning of the algorithm (e.g. from a map of the enviroment), but other information (e.g. the velocity vectors of moving obstacles) must be measured using sensors. The algorithms are tested in simulations and compared in different situations.

scholarly journals MOTION PLANNING IN SPACES WITH SMALL FUNDAMENTAL GROUPS

2010 ◽  
Vol 12 (01) ◽  
pp. 107-119 ◽  
Author(s):  
ARMINDO COSTA ◽  
MICHAEL FARBER
Keyword(s):  
Fundamental Group ◽  
Motion Planning ◽  
Cohomological Dimension ◽  
Upper Bounds ◽  
Topological Spaces ◽  
Topological Complexity ◽  
Fundamental Groups ◽  
Planning Algorithms

We establish sharp upper bounds for the topological complexity TC(X) of motion planning algorithms in topological spaces X such that the fundamental group is "small", i.e. when π1(X) is cyclic of order ≤ 3 or has small cohomological dimension.

scholarly journals Topological complexity and efficiency of motion planning algorithms

2018 ◽  
Vol 34 (4) ◽  
pp. 1679-1684
Author(s):  
Zbigniew Błaszczyk ◽  
José Gabriel Carrasquel-Vera
Keyword(s):  
Motion Planning ◽  
Topological Complexity ◽  
Planning Algorithms

Collision-free motion planning for the litchi-picking robot

2021 ◽  
Vol 185 ◽  
pp. 106151
Author(s):  
Lei Ye ◽  
Jieli Duan ◽  
Zhou Yang ◽  
Xiangjun Zou ◽  
Mingyou Chen ◽  
...  
Keyword(s):  
Motion Planning ◽  
Free Motion

Motion Planning for Mobile Robots: A Method for the Selection of a Combination of Motion-Planning Algorithms

2016 ◽  
Vol 23 (4) ◽  
pp. 107-117 ◽  
Author(s):  
J.J.M. Lunenburg ◽  
S.A.M. Coenen ◽  
G.J.L. Naus ◽  
M.J.G. van de Molengraft ◽  
M. Steinbuch
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Planning Algorithms ◽  
Selection Of
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