RIMAS: A Robust Indoor Mobile Autonomous System
Abstract
This paper presents RIMAS, an indoor mobile autonomous system designed for a wide variety of indoor applications. It is a low-cost, low-power, and highly robust system that can be deployed in a variety of indoor environments. RIMAS consists of a central base station, an array of sensors, and a navigation system that allow for autonomous navigation. The sensors used are low-cost, low-power, and highly accurate. The navigation system is based on a combination of laser-based SLAM and dead reckoning algorithms. The system is designed to be able to detect and avoid obstacles, and can also detect potential hazards in the environment. This paper describes the design and implementation of RIMAS, and provides results from a test deployment in a real-world environment.
Keywords: Autonomous system, indoor navigation, SLAM, obstacle detection, hazard detection
Introduction
Autonomous systems are becoming increasingly popular for a variety of applications, such as warehouse automation, home automation, and robotic exploration. Autonomous systems are typically composed of several components such as a central control unit, sensors, and an actuator. The main challenge in the design of such systems is the development of a robust navigation system that can autonomously navigate in an unknown environment and avoid obstacles and potential hazards.
RIMAS (Robust Indoor Mobile Autonomous System) is a low-cost, low-power, and highly robust indoor autonomous system designed for a wide variety of indoor applications. RIMAS consists of a central base station, an array of sensors, and a navigation system that allow for autonomous navigation. The base station is responsible for controlling the system and communicating with the sensors. The sensors are used to detect obstacles and potential hazards in the environment. The navigation system is based on a combination of laser-based SLAM (Simultaneous Localization and Mapping) and dead reckoning algorithms.
Design and Implementation
The RIMAS system is composed of a central base station, an array of sensors, and a navigation system. The base station is responsible for controlling the system and communicating with the sensors. It is equipped with a microcontroller, an Ethernet port, and a USB port for communicating with the sensors. The base station also includes a GPS unit for localization and a high-power radio for communication with the sensors.
The sensors used in the RIMAS system are low-cost, low-power, and highly accurate. The sensors are used to detect obstacles and potential hazards in the environment. The sensing package includes a laser scanner and an inertial measurement unit (IMU). The laser scanner is used to detect obstacles and potential hazards in the environment. The IMU is used to measure the orientation of the system.
The navigation system is based on a combination of laser-based SLAM and dead reckoning algorithms. The SLAM algorithm is used to create a map of the environment and to localize the system in the environment. The dead reckoning algorithm is used to control the system and navigate in the environment.
Results
The RIMAS system was tested in a real-world environment. The results demonstrate that the system is able to detect and avoid obstacles, and can also detect potential hazards in the environment. The results also show that the system is able to accurately localize itself in the environment.
Conclusion
This paper presented RIMAS, an indoor mobile autonomous system designed for a wide variety of indoor applications. The system is composed of a central base station, an array of sensors, and a navigation system that allow for autonomous navigation. The sensors used are low-cost, low-power, and highly accurate. The navigation system is based on a combination of laser-based SLAM and dead reckoning algorithms. The results from a test deployment in a real-world environment demonstrate that the system is able to detect and avoid obstacles, and can also detect potential hazards in the environment.
References
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