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Vehicle Controllers and Communication
Published in Iqbal Husain, Electric and Hybrid Vehicles, 2021
Communication modules in a microcontroller help a control unit communicate with external devices, such as back-up processors, shift registers, data loggers, data converters, diagnostics modules, monitoring devices, sensors or other controllers on the vehicle. Serial interface is often used in many automotive applications using communication modules such as CAN, SPI (serial peripheral interface) and LIN (local interconnect network). Serial communication modules transfer a group of data bits, one at a time, sequentially over a single data line. Microcontrollers may also be equipped with a parallel port that functions the same way as the serial port except that the data are in parallel format. Parallel communication is much faster than the serial communication, but requires address decoding. In automotive applications, parallel ports are used for external memory bus such as in DRAM or Flash.
Input–Output Organisation
Published in Pranabananda Chakraborty, Computer Organisation and Architecture, 2020
The port is a predefined junction on the bus where a resource or an additional circuit can be placed. A computer port is an addressable location with a specific address by which it is accessed. Usually, a resource (peripheral) is made connected with the port by using a specific cable, one end of which is connected with the resource (peripheral) and the other end with a connector is to be plugged into the predefined port. In some cases, the peripheral circuits are hard-wired to the port. Software of the peripheral device controls and monitors the port circuits by reading and writing to the port’s address. There are various types of ports available, but we will restrict our discussion in brief only to: Serial port;Parallel port;USB port.
PC Interfacing
Published in Ferat Sahin, Pushkin Kachroo, Practical and Experimental Robotics, 2017
In order to be able to program a robot for repetitive tasks or to integrate with sensors like cameras, we need to be able to connect the robot to a controller. We will use a PC as the robot controller for some robots in this book. Therefore, we need to interface the robot with a PC. There are many ways the robot can be connected to a PC. We can control the robot using relays by developing a sensor board that connects to some computer port, such as the parallel port or a USB port or a serial port. Serial ports are getting obsolete, so we will not discuss those in detail. In order to develop interface, we need to know how the parallel port works and how we can use it to connect to the robot. This is discussed below.
From Sensor-Space to Eigenspace – A Novel Real-Time Obstacle Avoidance Method for Mobile Robots
Published in IETE Journal of Research, 2022
Shyba Zaheer, Tauseef Gulrez, Imthias Ahamed Thythodath Paramabath
We simulated FCE for a differential drive mobile robot in ROS and Gazebo on a PC with virtual machine (VM-ware) based on Ubuntu Linux Core 4 Quad 3.4 GHz CPU, and 16.0 GB memory. Localization algorithm was assumed to be ideal. The turtlebot robot has a LiDAR to detect obstacles, where as LiDAR's angular range is . The cylinderical obstacles are tracked using FCE algorithm. The environment of the simulation is composed of environmental obstacles as shown in Figure 9. The environment includes fixed and moving obstacles. The controller for the robot is a ROS that gets the sensor data as input, over ROS topics, using these inputs various actions are determined, which consequently outputs a ROS message to the differential drive plug-in of the robot. For experimental validation purposes, the robot model selected was kabuki Turtlebot-II, which is ROS based robot and can perform advanced robotic tasks such as mapping, localization, etc. with the following specifications: Maximum translational velocity: 70 cm/sMaximum rotational velocity: 180 deg/sPayload: 5 kg (hard floor), 4 kg (carpet)PC Connection: USB or via RX/TX pins of the parallel portMotor Overload Detection: disables power on detecting high current Odometry: 52 ticks/encoder rev, 2578.33 ticks/wheel rev, 11.7 ticks/mmSensor Data Rate: 50 Hz