Benchmark on robotic motion planning algorithms in a drilling task

Sampling-based robotic motion planning algorithms have been the key concept of programming robot motion as they are validated to be probabilistically complete. Thus, numerous research studies have been carried out to continuously improve these algorithms to lower the cost, which includes the time ta...

Täydet tiedot

Bibliografiset tiedot
Päätekijä: Lim, Joyce Xin Yan
Muut tekijät: Pham Quang Cuong
Aineistotyyppi: Final Year Project (FYP)
Kieli:English
Julkaistu: 2018
Aiheet:
Linkit:http://hdl.handle.net/10356/75164
_version_ 1826126370525151232
author Lim, Joyce Xin Yan
author2 Pham Quang Cuong
author_facet Pham Quang Cuong
Lim, Joyce Xin Yan
author_sort Lim, Joyce Xin Yan
collection NTU
description Sampling-based robotic motion planning algorithms have been the key concept of programming robot motion as they are validated to be probabilistically complete. Thus, numerous research studies have been carried out to continuously improve these algorithms to lower the cost, which includes the time taken to solve the query or the trajectory execution time. This report covers the benchmark of sampling-based motion planners, such as single-query and multi-query planners, in a static environment to determine whether reusing the roadmap of multi-query planners will reduce the cost of solving multiple queries, as compared to single-query planners where new trees are constructed for every query. The benchmark requires the use of Open Robotics Automation Virtual Environment (OpenRAVE), which provides an environment to simulate robot motion with their planners, and Open Motion Planning Library (OMPL) which has a variety of motion planners. The study also includes the integration of OMPL into OpenRAVE since the benchmark is carried out by using planners from not only OpenRAVE, but OMPL as well. Specifically, the benchmark will cover the total time taken to solve the queries with smoothing, total trajectory execution time and robustness of the planners. Also, the programming language used in this project is Python.
first_indexed 2024-10-01T06:51:34Z
format Final Year Project (FYP)
id ntu-10356/75164
institution Nanyang Technological University
language English
last_indexed 2024-10-01T06:51:34Z
publishDate 2018
record_format dspace
spelling ntu-10356/751642023-03-04T18:45:52Z Benchmark on robotic motion planning algorithms in a drilling task Lim, Joyce Xin Yan Pham Quang Cuong School of Mechanical and Aerospace Engineering Robotics Research Centre DRNTU::Engineering Sampling-based robotic motion planning algorithms have been the key concept of programming robot motion as they are validated to be probabilistically complete. Thus, numerous research studies have been carried out to continuously improve these algorithms to lower the cost, which includes the time taken to solve the query or the trajectory execution time. This report covers the benchmark of sampling-based motion planners, such as single-query and multi-query planners, in a static environment to determine whether reusing the roadmap of multi-query planners will reduce the cost of solving multiple queries, as compared to single-query planners where new trees are constructed for every query. The benchmark requires the use of Open Robotics Automation Virtual Environment (OpenRAVE), which provides an environment to simulate robot motion with their planners, and Open Motion Planning Library (OMPL) which has a variety of motion planners. The study also includes the integration of OMPL into OpenRAVE since the benchmark is carried out by using planners from not only OpenRAVE, but OMPL as well. Specifically, the benchmark will cover the total time taken to solve the queries with smoothing, total trajectory execution time and robustness of the planners. Also, the programming language used in this project is Python. Bachelor of Engineering (Mechanical Engineering) 2018-05-28T09:19:54Z 2018-05-28T09:19:54Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/75164 en Nanyang Technological University 42 p. application/pdf
spellingShingle DRNTU::Engineering
Lim, Joyce Xin Yan
Benchmark on robotic motion planning algorithms in a drilling task
title Benchmark on robotic motion planning algorithms in a drilling task
title_full Benchmark on robotic motion planning algorithms in a drilling task
title_fullStr Benchmark on robotic motion planning algorithms in a drilling task
title_full_unstemmed Benchmark on robotic motion planning algorithms in a drilling task
title_short Benchmark on robotic motion planning algorithms in a drilling task
title_sort benchmark on robotic motion planning algorithms in a drilling task
topic DRNTU::Engineering
url http://hdl.handle.net/10356/75164
work_keys_str_mv AT limjoycexinyan benchmarkonroboticmotionplanningalgorithmsinadrillingtask