Autonomous Mobile Platform
The first version of a simple AMP was built in SUT from a Pirate-4WD Mobile platform and Romeo All-in-One Controller, which was responsible for the engine control and a Raspberry Pi RPI model B + NOOBS, which was responsible for the control of the system. Communication with the PC was realised via a Wi-Fi solution that was integrated with the Raspberry Pi.
Communication between the Raspberry Pi and Controller was realised using an RS232 interface. The mobile platform was equipped with a Wi-Fi module and encoders. In the next stage, the mobile platform was equipped with ultrasound, a gyroscope, an accelerometer, GPS, a camera and a connection for advanced modules, radar and lidar systems using the CAN interface. Communication with the other sensors was realised using SPI, I2C, IO interfaces. The entire system was supplied from 7,4V 3300 mAh accumulator.
The first test allowed the work in the manual mode to be confirmed. The AMP allow forward and backward movement, left and right turns and rotating in place. The Raspian Linux system was installed on the RaspberryPI, which allowed it to communicate with the AMP from terminal.
The control functions were implemented as Python scripts with this instruction list:
- L / R – Rotate in place left / right
- W / S – Move forward / backward
- A / D – Turn to the front left / right
- LED ON / OFF – control of the green LEDs on Romeo
Access to the AMP control was realised using an HTTP server. To create on Raspberry Pi the HTTP server and communication were used Tornado framework. When an operator puts an AMP IP address with 8888 port on the browser, it opens the control page of the AMP. At this moment, he can remote manually control the AMP by using the corresponding keys to the functions that were described above.
At present, to the system are connecting sensors, what will allow go to the next stages of realization of the project.
The information’s from these sensors are processed by Raspberry Pi and are sufficient to detect obstacles, determine the distance to obstacles and prepare actions to avoid the obstacles. The data obtained from sensors allow for the development of automatic obstacle avoidance functions for mobile platforms. The vehicle has to rotate around on its vertical axis and take the measurements during this rotation for measure the distance to obstacles in other directions.
The deep obstacle, algorithm A1.
The deep obstacle, algorithm A2.
The round obstacle, algorithm A1.
The ro und obstacle, algorithm A2.
The research station consisted of a Forbot 1.4A mobile platform from Roboterwerk, an STM32F3 Discovery board, a Raspberry PI and a PC. The mobile platform consisted of two brushless 3-phase BLDC motors that were controlled by two SMCI36 motor. Control of the engines was realised using the STM32. Communication between the STM32 and SMCI36 was realised using a clock signal.
Presentation on sience nights