Optimization of robot configurations for motion planning in industrial riveting

Author(s):  
Hakan Girgin ◽  
Teguh Santoso Lembono ◽  
Radu Cirligeanu ◽  
Sylvain Calinon
Author(s):  
K Jiang ◽  
L D Seneviratne ◽  
S W E Earles

This paper presents a new motion planning approach, including reversal manoeuvres, for car-like robots subject to non-holonomic constraints. The paper presents a complete path planning algorithm and describes the procedure for constructing a collision-free path for a mobile robot constrained by its rectangular shape and kinematics. Emphasis is made on the techniques of reversal transfers, which are used to compensate the limited manoeuvrability of a car-like robot. The approach works entirely in the workspace, as opposed to building a higher dimensional configuration space (C-space). It starts by constructing a visibility graph and finding the shortest path for a point robot and then detects areas where collision may occur by minimum distance calculations between obstacles and between the selected path and obstacles. Robot configurations are placed along the shortest path and lemmas are developed for ascertaining transfers from one robot configuration to another. The transfer techniques include direct, indirect and reversal manoeuvres, and ensure that the path is feasible for the robot to travel with a given steering limit. The process runs in time O(nk + n log n) for k obstacles and n vertices. The algorithm is tested in computer simulations and results are given, demonstrating the versatility of the algorithm.


2020 ◽  
Vol 39 (5) ◽  
pp. 598-616
Author(s):  
Tony Dear ◽  
Blake Buchanan ◽  
Rodrigo Abrajan-Guerrero ◽  
Scott David Kelly ◽  
Matthew Travers ◽  
...  

Conventional approaches in prescribing controls for locomoting robots assume control over all input degrees of freedom (DOFs). Many robots, such as those with non-holonomic constraints, may not require or even allow for direct command over all DOFs. In particular, a snake robot with more than three links with non-holonomic constraints cannot achieve arbitrary configurations in all of its joints while simultaneously locomoting. For such a system, we assume partial command over a subset of the joints, and allow the rest to evolve according to kinematic chained and dynamic models. Different combinations of actuated and passive joints, as well as joints with dynamic elements such as torsional springs, can drastically change the coupling interactions and stable oscillations of joints. We use tools from nonlinear analysis to understand emergent oscillation modes of various robot configurations and connect them to overall locomotion using geometric mechanics and feedback control for robots that may not fully utilize all available inputs. We also experimentally verify observations and motion planning results on a physical non-holonomic snake robot.


Author(s):  
Beomjoon Kim ◽  
Leslie Pack Kaelbling ◽  
Tomás Lozano-Pérez

We propose an actor-critic algorithm that uses past planning experience to improve the efficiency of solving robot task-and-motion planning (TAMP) problems. TAMP planners search for goal-achieving sequences of high-level operator instances specified by both discrete and continuous parameters. Our algorithm learns a policy for selecting the continuous parameters during search, using a small training set generated from the search trees of previously solved instances. We also introduce a novel fixed-length vector representation for world states with varying numbers of objects with different shapes, based on a set of key robot configurations. We demonstrate experimentally that our method learns more efficiently from less data than standard reinforcementlearning approaches and that using a learned policy to guide a planner results in the improvement of planning efficiency.


2006 ◽  
Author(s):  
Jonathan Vaughan ◽  
Steven Jax ◽  
David A. Rosenbaum
Keyword(s):  

Author(s):  
Ioan Sucan ◽  
Sachin Chitta
Keyword(s):  


1995 ◽  
Author(s):  
Sumanta Guha ◽  
Rama D. Puvvada ◽  
Deepti Suri ◽  
Ichiro Suzuki

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