DocumentCode :
663690
Title :
Characterizing and addressing dynamic singularities in the time-optimal path parameterization algorithm
Author :
Quang-Cuong Pham
Author_Institution :
Sch. of Mech. & Aerosp. Eng., Nanyang Technol. Univ., Singapore, Singapore
fYear :
2013
fDate :
3-7 Nov. 2013
Firstpage :
2357
Lastpage :
2363
Abstract :
The algorithm for finding the time-optimal parameterization of a given path subject to dynamics constraints developed mostly in the 80´s and 90´s plays a central role in a number of important robotic theories and applications. A critical issue in its implementation is associated with the so-called dynamic singularities, i.e. the points where the maximum velocity curve is continuous but undifferentiable and where the minimum and maximum accelerations are not naturally defined. Since such singularities arise in most real-world problem instances, characterizing and addressing them appropriately is of particular interest. Yet, from original articles to reference textbooks, this has not yet been done completely correctly. The contribution of the present article is two-fold. First, we derive a complete characterization of dynamic singularities. In particular, we show that not all zero-inertia points are dynamically singular. Second, we suggest how to appropriately address these singularities. In particular, we derive the analytic expressions of the correct optimal backward and forward accelerations from such points.
Keywords :
robot dynamics; dynamic singularities; dynamics constraints; forward accelerations; maximum velocity curve; reference textbooks; robotic theories; time optimal path parameterization algorithm; zero inertia points; Acceleration; Aerodynamics; Equations; Heuristic algorithms; Switches; Vectors; Vehicle dynamics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on
Conference_Location :
Tokyo
ISSN :
2153-0858
Type :
conf
DOI :
10.1109/IROS.2013.6696687
Filename :
6696687
Link To Document :
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