TY - EJOU
AU - Baranauskas, Virginijus
AU - Jakas, Žydrūnas
AU - Šarkauskas, Kastytis Kiprijonas
AU - Bartkevičius, Stanislovas
AU - Dervinis, Gintaras
AU - Dervinienė, Alma
AU - Balaševičius, Leonas
AU - Raudonis, Vidas
AU - Urniežius, Renaldas
AU - Repšytė, Jolanta
TI - Mobile Robots’ Collision Prediction Based on Virtual Cocoons
T2 - Intelligent Automation \& Soft Computing
PY - 2022
VL - 32
IS - 3
SN - 2326-005X
AB - The research work presents a collision prediction method of mobile robots. The authors of the work use so-called, virtual cocoons to evaluate the collision criteria of two robots. The idea, mathematical representation of the calculations and experimental simulations are presented in the paper work. A virtual model of the industrial process with moving mobile robots was created. Obstacle avoidance was not solved here. The authors of the article were working on collision avoidance problem solving between moving robots. Theoretical approach presents mathematical calculations and dependences of path angles of mobile robots. Experimental simulations, using the software Centaurus CPN, based on colored Petri nets, has shown, that the possible conflict can be predicted in advance using calculations of the angle of movement of two possibly colliding cocoons. Authors of the paper presents and explains experimental simulations, where robots are moving in different path angles, which intersects each other. Proposed collision avoidance algorithm solves collision avoidance task using several possibilities. Software Centaurus CPN gives possibility to stop simulation of manufacturing process in the place where it finds possible collision between two cocoons. In order to check correctness of proposed collision prediction and avoidance algorithm, further simulation is done step by step, while situation is solved. Simulated manufacturing process is continued till new possible collision is obtained.
KW - Robots control; prediction of conflicts; multi-robot system; protective sheath “cocoon”; robot motion control
DO - 10.32604/iasc.2022.022288