Foraging Ant Motion Planning for Articulated Robots

2006 ◽  
Author(s):  
Mohd Mohamad ◽  
Matthew Dunnigan ◽  
Nicholas Taylor
Keyword(s):  
Motion Planning ◽  
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.

scholarly journals Adaptation Algorithm of Geometric Graphs for Robot Motion Planning in Dynamic Environments

2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Jae-Han Park ◽  
Ji-Hun Bae ◽  
Moon-Hong Baeg
Keyword(s):  
Motion Planning ◽  
Configuration Space ◽  
Distributed Processing ◽  
Graph Algorithm ◽  
Dynamic Environments ◽  
Robot Motion ◽  
Geometric Graphs ◽  
Adaptation Algorithm ◽  
Adaptation Mechanism ◽  
Articulated Robots

This study proposes an adaptive graph algorithm for collision-free motion planning of articulated robots in dynamic environments. For this purpose, deformations of the configuration space were analyzed according to the changes of the workspace using various simulations. Subsequently, we adopted the principles of gas motion dynamics in our adaptation algorithm to address the issue of the deformation of the configuration space. The proposed algorithm has an adaptation mechanism based on expansive repulsion and sensory repulsion, and it can be performed to provide the entire adaptation using distributed processing. The simulation results confirmed that the proposed method allows the adaptation of the roadmap graph to changes of the configuration space.

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