T-3-3-4 Optimum trajectory planning in order to reduce vibration of one-link flexible arm based on first natural frequency

2002 ◽  
Vol 2002 (0) ◽  
pp. 266-273
Author(s):  
Shiro Arii ◽  
Masafumi Inoue ◽  
Hiroyuki Tane ◽  
Hiroshi Mizumoto
Keyword(s):  
Natural Frequency ◽  
Trajectory Planning ◽  
Optimum Trajectory ◽  
Flexible Arm

scholarly journals Numerical Aspects and Performances of Trajectory Planning Methods of Flexible Axes

2006 ◽  
Vol 1 (4) ◽  
pp. 35 ◽  
Author(s):  
Jean-Yves Dieulot ◽  
Issam Thimoumi ◽  
Frédéric Colas ◽  
Richard Béarée
Keyword(s):  
Optimal Control ◽  
Path Planning ◽  
Natural Frequency ◽  
Trajectory Planning ◽  
Input Shaping ◽  
Robot Arm ◽  
Frequency Mismatch ◽  
Planning Methods ◽  
Real Robot ◽  
Theoretical Results

Adequate Path Planning design is an important stage for controlling flexible axes because it may allow to cancel vibrations induced by oscillating modes. Among bang-bang profiles which are linked to optimal control, jerk assignment (acceleration derivative) and input shapers have been investigated. Theoretical results show the performance and robustness with respect to natural frequency mismatch. Practical validations on a real robot arm show the relevance of the jerk algorithm which is more robust with the same productivity performances as input shaping techniques.

scholarly journals An algorithm of near-optimum trajectory planning for manipulators.

1990 ◽  
Vol 56 (527) ◽  
pp. 1881-1886
Author(s):  
Motoji YAMAMOTO ◽  
Shinya MARUSHIMA ◽  
Akira MOHRI
Keyword(s):  
Trajectory Planning ◽  
Optimum Trajectory

Optimum Trajectory Planning for Multi-Rotor UAV Relays with Tilt and Antenna Orientation Variations

2021 ◽  
Author(s):  
Daniel Bonilla Licea ◽  
Giuseppe Silano ◽  
Mounir Ghogho ◽  
Martin Saska
Keyword(s):  
Trajectory Planning ◽  
Optimum Trajectory

Evolutionary Collision Free Optimal Trajectory Planning for Mobile Robots

1999 ◽  
Vol 11 (2) ◽  
pp. 153-164 ◽  
Author(s):  
M.M.A. Hashem ◽  
◽  
Keigo Watanabe ◽  
Kiyotaka Izumi ◽  
◽  
...  
Keyword(s):  
Mobile Robots ◽  
Evolutionary Algorithm ◽  
Trajectory Planning ◽  
Fitness Function ◽  
Coordinate Frame ◽  
Planning Problem ◽  
Evolutionary Trajectory ◽  
Optimum Trajectory ◽  
Insertion And Deletion ◽  
Sensor Modeling

We present an evolutionary trajectory planning method for mobile robots following a novel evolution strategy (NES) algorithm. The 2-D trajectory planning problem of a mobile robot among polygonal obstacles is formulated as a constrained time-optimum control problem considering motion. Unlike traditional evolutionary representation, special representation of individuals and crossover are used for the evolutionary search. Swapping crossover, insertion, and deletion mutations are used as background operators for maximum evolutionary algorithm flexibility. Polygonal obstacles in the world coordinate frame are modeled as circles from visibility and sensor modeling concepts. An appropriate cost (fitness) function is constructed as the only link between the evolutionary algorithm and environment. Our proposed evolution is effective for collision-free optimum trajectory planning in robot simulation within a heavily constrained (obstacle) environment.

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