Collision Avoidance System with Model Predictive Control for Mobile Robot Navigation

Achmad Imam Sudianto; Muhammad Aziz Muslim; Mohammad Rusli

doi:10.1109/ICSINTESA56431.2022.10041582

Collision Avoidance System with Model Predictive Control for Mobile Robot Navigation

Achmad Imam Sudianto^*
, Muhammad Aziz Muslim
, Mohammad Rusli

^*Corresponding author for this work

Faculty of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Mobile robot mission always begins with the movement of the mobile robot to a certain location where the robot performs its duties. To carry out these movements, a control method is needed to move the mobile robot's actuator (in the form of wheels or legs) and understand the situation around the robot (perception). This research aims to realize a method that can detect obstacle and distances as well as regulate their movement. The Model Predictive Control (MPC) method is proposed to assist control as part of a low-level controller. This research proposes the use of the NN method to detect obstacles and also as part of the high-level controller on the robot. The results obtained from this method, are the smaller the horizon value with a value of 10, the time needed to reach the desired coordinate point is shorter with a result of 57 seconds.

Original language	English
Title of host publication	2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	204-209
Number of pages	6
ISBN (Electronic)	9781665472883
DOIs	https://doi.org/10.1109/ICSINTESA56431.2022.10041582
Publication status	Published - 2022
Event	2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022 - Virtual, Online, Indonesia Duration: 10 Nov 2022 → 12 Nov 2022

Publication series

Name	2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022

Conference

Conference	2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022
Country/Territory	Indonesia
City	Virtual, Online
Period	10/11/22 → 12/11/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

autonomous vehicle
lidar
Model predictive control
neural network
ros

Access to Document

10.1109/ICSINTESA56431.2022.10041582

Cite this

Sudianto, A. I., Muslim, M. A., & Rusli, M. (2022). Collision Avoidance System with Model Predictive Control for Mobile Robot Navigation. In 2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022 (pp. 204-209). (2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSINTESA56431.2022.10041582

Sudianto, Achmad Imam ; Muslim, Muhammad Aziz ; Rusli, Mohammad. / Collision Avoidance System with Model Predictive Control for Mobile Robot Navigation. 2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 204-209 (2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022).

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title = "Collision Avoidance System with Model Predictive Control for Mobile Robot Navigation",

abstract = "Mobile robot mission always begins with the movement of the mobile robot to a certain location where the robot performs its duties. To carry out these movements, a control method is needed to move the mobile robot's actuator (in the form of wheels or legs) and understand the situation around the robot (perception). This research aims to realize a method that can detect obstacle and distances as well as regulate their movement. The Model Predictive Control (MPC) method is proposed to assist control as part of a low-level controller. This research proposes the use of the NN method to detect obstacles and also as part of the high-level controller on the robot. The results obtained from this method, are the smaller the horizon value with a value of 10, the time needed to reach the desired coordinate point is shorter with a result of 57 seconds.",

keywords = "autonomous vehicle, lidar, Model predictive control, neural network, ros",

author = "Sudianto, \{Achmad Imam\} and Muslim, \{Muhammad Aziz\} and Mohammad Rusli",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022 ; Conference date: 10-11-2022 Through 12-11-2022",

year = "2022",

doi = "10.1109/ICSINTESA56431.2022.10041582",

language = "English",

series = "2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "204--209",

booktitle = "2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022",

}

Sudianto, AI, Muslim, MA & Rusli, M 2022, Collision Avoidance System with Model Predictive Control for Mobile Robot Navigation. in 2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022. 2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022, Institute of Electrical and Electronics Engineers Inc., pp. 204-209, 2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022, Virtual, Online, Indonesia, 10/11/22. https://doi.org/10.1109/ICSINTESA56431.2022.10041582

Collision Avoidance System with Model Predictive Control for Mobile Robot Navigation. / Sudianto, Achmad Imam; Muslim, Muhammad Aziz ; Rusli, Mohammad.
2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 204-209 (2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Collision Avoidance System with Model Predictive Control for Mobile Robot Navigation

AU - Sudianto, Achmad Imam

AU - Muslim, Muhammad Aziz

AU - Rusli, Mohammad

PY - 2022

Y1 - 2022

N2 - Mobile robot mission always begins with the movement of the mobile robot to a certain location where the robot performs its duties. To carry out these movements, a control method is needed to move the mobile robot's actuator (in the form of wheels or legs) and understand the situation around the robot (perception). This research aims to realize a method that can detect obstacle and distances as well as regulate their movement. The Model Predictive Control (MPC) method is proposed to assist control as part of a low-level controller. This research proposes the use of the NN method to detect obstacles and also as part of the high-level controller on the robot. The results obtained from this method, are the smaller the horizon value with a value of 10, the time needed to reach the desired coordinate point is shorter with a result of 57 seconds.

AB - Mobile robot mission always begins with the movement of the mobile robot to a certain location where the robot performs its duties. To carry out these movements, a control method is needed to move the mobile robot's actuator (in the form of wheels or legs) and understand the situation around the robot (perception). This research aims to realize a method that can detect obstacle and distances as well as regulate their movement. The Model Predictive Control (MPC) method is proposed to assist control as part of a low-level controller. This research proposes the use of the NN method to detect obstacles and also as part of the high-level controller on the robot. The results obtained from this method, are the smaller the horizon value with a value of 10, the time needed to reach the desired coordinate point is shorter with a result of 57 seconds.

KW - autonomous vehicle

KW - lidar

KW - Model predictive control

KW - neural network

KW - ros

UR - https://www.scopus.com/pages/publications/85149566044

U2 - 10.1109/ICSINTESA56431.2022.10041582

DO - 10.1109/ICSINTESA56431.2022.10041582

M3 - Conference contribution

AN - SCOPUS:85149566044

T3 - 2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022

SP - 204

EP - 209

BT - 2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022

Y2 - 10 November 2022 through 12 November 2022

ER -

Sudianto AI, Muslim MA , Rusli M. Collision Avoidance System with Model Predictive Control for Mobile Robot Navigation. In 2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 204-209. (2022 International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2022). doi: 10.1109/ICSINTESA56431.2022.10041582

Collision Avoidance System with Model Predictive Control for Mobile Robot Navigation

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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