PERCEPTION AND AUTONOMOUS NAVIGATION SYSTEM DESIGN AND IMPLEMENTATION OF UNMANNED GROUND VEHICLE USING ROBOT OPERATING SYSTEM FRAMEWORK
Autonomous robots are intelligent machines capable of performing tasks in the world by themselves, without explicit human control. Autonomous mobile robots, currently, come in a wide range of form factors. One application of the use of autonomous robots is Mechanical Handling Equipment in the...
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Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/56161 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | Autonomous robots are intelligent machines capable of performing tasks in the
world by themselves, without explicit human control. Autonomous mobile robots,
currently, come in a wide range of form factors. One application of the use of
autonomous robots is Mechanical Handling Equipment in the warehouse area. The
transformation from manual product handling to automatic is carried out as an
effort to automate warehousing. In this paper, we will implement a prototype of an
autonomous vehicle capable of moving from one location to another in an indoor
warehouse environment. Implementation begins by dividing the navigation system
into three sub-systems, namely perception, decision maker, and actuator.
Perception subsystem designed in order to be able to perceive the environment
around the vehicle. An understanding of the surrounding environment is achieved
based on the data that has been acquired by the sensors. Decision maker subsystem
is designed in order to be able to determine the best alternative based on the tasks
given and the information received along the way. The actuator subsystem is
designed to be able to convert digital commands into a hardware movement, such
as a motor or steering wheel. The conclusion obtained from this paper is that the
vehicle is able to understand the state of the surrounding environment and is able
to move from one location to another with certain errors, which are caused by
distortion and sensor noise. |
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