An adaptive framework for 'single shot' motion planning: a self-tuning system for rigid and articulated robots

2002 ◽  
Author(s):  
D. Vallejo ◽  
I. Remmler ◽  
N.M. Amato
Keyword(s):  
Motion Planning ◽  
Single Shot ◽  
Self Tuning ◽  
Adaptive Framework ◽  
Articulated Robots

scholarly journals Self-Tuning Control for Articulated Robots Using the Plestan’s Method

2021 ◽  
Vol 22 (4) ◽  
pp. 557-566
Author(s):  
Maolin Jin ◽  
Jinoh Lee ◽  
Kap-Ho Seo ◽  
Jin-Ho Suh
Keyword(s):  
Self Tuning ◽  
Articulated Robots

Safety-oriented path planning for articulated robots

Robotica ◽  
2013 ◽  
Vol 31 (6) ◽  
pp. 861-874 ◽  
Author(s):  
Bakir Lacevic ◽  
Paolo Rocco
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Case Studies ◽  
Configuration Space ◽  
Safety Margin ◽  
Robotic Manipulators ◽  
Heuristic Function ◽  
Oriented Path ◽  
Planning Algorithms ◽  
Articulated Robots

SUMMARYThis work presents an approach to motion planning for robotic manipulators that aims at improving path quality in terms of safety. Safety is explicitly assessed using the quantity called danger field. The measure of safety can easily be embedded into a heuristic function that guides the exploration of the free configuration space. As a result, the resulting path is likely to have substantially higher safety margin when compared to one obtained by regular planning algorithms. To this end, four planning algorithms have been proposed. The first planner is based on volume trees comprised of bubbles of free configuration space, while the remaining ones represent modifications of classical sampling-based algorithms. Several numerical case studies are carried out to validate and compare the performance of the presented algorithms with respect to classical planners. The results indicate significantly lower danger metric for paths obtained by safety-oriented planners even with some decrease in running time.

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