Louis, Dylan and Rusyadi, Rusman and Galinium, Maulahikmah (2022) IMPLEMENTATION OF VISUAL INERTIAL ODOMETRY CONCEPT FOR OUTDOOR AUTONOMOUS MOBILE ROBOT LOCALIZATION AND NAVIGATION BASED ON ROS2. Bachelor thesis, Swiss German University.

	Text MT_Dylan Louis_1.pdf Restricted to Repository staff only Download (485kB)
	Text MT_Dylan Louis_2.pdf Restricted to Repository staff only Download (1MB)
	Text MT_Dylan Louis_3.pdf Restricted to Repository staff only Download (4MB)
	Text MT_Dylan Louis_4.pdf Restricted to Repository staff only Download (5MB)
	Text MT_Dylan Louis_5.pdf Restricted to Repository staff only Download (331kB)
	Text MT_Dylan Louis_REF.pdf Download (2MB)
	Text MT_Dylan Louis_TOC.pdf Download (1MB)

Abstract

Logistical operation in various industries are progressively getting replaced by the utilization of Autonomous Mobile Robots (AMR), that majorly focus on last-mile delivery in an indoor environment. On the other hand, demands of operating AMR in an outdoor scenario gradually increase over time. Thus, this thesis focuses on the development of AMR based on ROS2, that is suitable for operation in outdoor settings, with a specialization of implementing the concept of Visual Inertial Odometry (VIO) by using Intel Realsense T265 tracking camera as an alternative approach for mobile robot localization and navigation that usually utilizes a fusion of mechanically driven rotary encoders and IMU unit. The odometry data generated from the tracking camera displays an idle pose deviation of ± 0.05m with an average error percentage of 28.60% when subjected to linear movement and operated outdoors under a sunny condition. Ultimately, the outdoor AMR is capable to localize itself by projecting its pose by utilizing the odometry data generated by the tracking camera, with a further integration that successfully enables the operation of autonomous navigation. On the whole, the results of this thesis are feasible as findings and source of data that could be further elaborated on associated mobile robot developments.

Item Type:	Thesis (Bachelor)
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ210 Robots (General)
Divisions:	Faculty of Engineering and Information Technology > Department of Mechatronics Engineering
Depositing User:	Mr Arinton Sinaga
Date Deposited:	11 Dec 2024 03:41
Last Modified:	11 Dec 2024 03:41
URI:	http://repository.sgu.ac.id/id/eprint/2705

Actions (login required)

View Item