Grabusts, Pēteris

Thumbnail Image
Preferred name
Grabusts, Pēteris
Official Name
Grabusts, Pēteris
Alternative Name
Peter Grabusts
Pēteris Grabusts
Main Affiliation
Email
peteris.grabusts@rta.lv
Scopus Author ID
55835004700
Researcher ID
AAU-5594-2021

Research Output

Filters

2
21
2
2
Reset filters

Settings

Now showing 1 - 2 of 2
  • Publication
    Motion Planning of an Autonomous Robot in Closed Space with Obstacles
    (2012)
    Edvards Valbahs
    ;
    Grabusts, Pēteris 
    The paper deals with path planning software for a mobile robotic platform. The aim of the research paper is to analyse path planning algorithms that comprise the design of simulation software. The software is necessary as an environment model to obtain the simulation data. The simulation application is based on the Rapidly-Exploring Random Tree (RRT) algorithm and Simulated Annealing (SA). The results of the thorough analysis have been used to achieve optimal path planning algorithms.
  • Publication
    Non - Euclidean Metric and Path Planning
    (2016)
    Edvards Valbahs
    ;
    Grabusts, Pēteris 
    In order to achieve the wide range of the robotic application it is necessary to provide iterative motions among points of the goals. For instance, in the industry mobile robots can replace any components between a storehouse and an assembly department. Ammunition replacement is widely used in military services. Working place is possible in ports, airports, waste site and etc. Mobile agents can be used for monitoring if it is necessary to observe control points in the secret place. The paper deals with path planning programme for mobile robots. The aim of the research paper is to analyse motion-planning algorithms that contain the design of modelling programme. The programme is needed as environment modelling to obtain the simulation data. The simulation data give the possibility to conduct the wide analyses for selected algorithm. Analysis means the simulation data interpretation and comparison with other data obtained using the motion-planning. The results of the careful analysis were considered for optimal path planning algorithms. The experimental evidence was proposed to demonstrate the effectiveness of the algorithm for steady covered space. The results described in this work can be extended in a number of directions, and applied to other algorithms.