Leader–Follower Approach for Non-Holonomic Mobile Robots Based on Extended Kalman Filter Sensor Data Fusion and Extended On-Board Camera Perception Controlled with Behavior Tree

Arpit Joon; Wojciech Kowalczyk

doi:10.3390/s23218886

System Informacji Naukowej Politechniki Poznańskiej

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Artykuł

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Tytuł

Leader–Follower Approach for Non-Holonomic Mobile Robots Based on Extended Kalman Filter Sensor Data Fusion and Extended On-Board Camera Perception Controlled with Behavior Tree

Autorzy

Arpit Joon (WARiE) ^{[ 1 ][ 2.2 ][ SzD ]}
Wojciech Kowalczyk (WARiE) ^{[ 2 ][ 2.2 ][ P ]}

^{[ 1 ]} Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | ^{[ 2 ]} Instytut Automatyki i Robotyki, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | ^{[ SzD ]} doktorant ze Szkoły Doktorskiej | ^{[ P ]} pracownik

Dyscyplina naukowa (Ustawa 2.0)

[2.2] Automatyka, elektronika, elektrotechnika i technologie kosmiczne

Rok publikacji

2023

Opublikowano w

Sensors

Rocznik: 2023 | Tom: vol. 23 | Numer: iss. 21

Typ artykułu

artykuł naukowy

Język publikacji

angielski

Słowa kluczowe

EN

sensor data fusion
fiducial marker
extended kalman filter
mobile robots
leader–follower control
ROS
landmarks
behavior tree

Streszczenie

EN This paper presents a leader–follower mobile robot control approach using onboard sensors. The follower robot is equipped with an Intel RealSense camera mounted on a rotating platform. Camera observations and ArUco markers are used to localize the robots to each other and relative to the workspace. The rotating platform allows the expansion of the perception range. As a result, the robot can use observations that are not within the camera’s field of view at the same time in the localization process. The decision-making process associated with the control of camera rotation is implemented using behavior trees. In addition, measurements from encoders and IMUs are used to improve the quality of localization. Data fusion is performed using the EKF filter and allows the user to determine the robot’s poses. A 3D-printed cuboidal tower is added to the leader robot with four ArUco markers located on its sides. Fiducial landmarks are placed on vertical surfaces in the workspace to improve the localization process. The experiments were performed to verify the effectiveness of the presented control algorithm. The robot operating system (ROS) was installed on both robots.

Data udostępnienia online

01.11.2023

Strony (od-do)

8886-1 - 8886-20

DOI

10.3390/s23218886

URL

https://www.mdpi.com/1424-8220/23/21/8886

Uwagi

Article Number: 8886

Typ licencji

CC BY (uznanie autorstwa)