In [8] a low-cost RC toy car receives commands from a PC in order to follow a path. The car is shown in Figure 2.1. The Zigbee communication protocol and an ATmega 162 microcontroller are used in this car. An OptiTrack/Vicon system, which consists of 12 cameras, is used to get the positions and orientations of the car. It is stated that the Vicon system is more accurate as it can cover more area and has a larger range compared to the OptiTrack system. The need for robust control algorithms is described, as the RC car does not have precise control of its steering mechanism. As the battery discharges very quickly, the duty cycles which are used to steer the car need to be adjusted constantly in [8]. Also the car’s steering control does not respond correctly if the instructions are sent at a higher frequency. In [8] it is also observed that the surface friction has a large effect on the RC car’s motion. From [8] it can be learned that the use of toy cars, which are not build for a research application can give issues similar to the ones observed in TruckLab.
Figure 2.1: low-cost RC toy car [8]
CHAPTER 2. LITERATURE SURVEY
Car manufacturer Audi developed a 1:8 scale model vehicle specifically for the Audi Au-tonomous Driving Cup [10]. The scale model is shown in Figure 2.2. Students participate in this event to develop autonomous driving functions. This vehicle has two separate energy circuits.
One circuit for the ’mini-ITX board’ computer and one for the brushless motor. This brushless motor is controlled by a cruise control which gives the ability to drive forward, reverse and brake in a controlled manner, also at low speeds. The digital steering servo has integrated control, therefore a separate measurement of the steering angle is not necessary. Battery cell voltages can be monitored by an Arduino. The car is equipped with lidar, two mono video cameras, five ultrasonic sensors, wheel speed sensors and a 9-axis motion tracking sensor. The software used is ADTF(Automotive Data and Time-triggered Framework). Reference [10] shows the interest of car manufacturers in autonomous driving and gives inspiration for further development of the scaled tractor semitrailers used in the TruckLab.
Figure 2.2: scale model specifically build for AADC [10]
In [9] an autonomous RC car is discussed, which is the result of an interdisciplinary project at a university in Germany. It is stated that engineers always have to make a compromise between the power consumption and the available computing power. This trade off leads to heterogeneous computing systems which offer a beneficial power consumption. Learning how to integrate such systems into vehicles, is one of the aspects which can be investigated by means of a scaled RC car.
The result is a car that has a monocular camera, a lidar, a radar, differential GPS and an IMU.
The sensor data is communicated to the processing board by means of UART. The ZedBoard pro-cessing board consists of an Altera Cyclone 5 SOC with an FPGA and a dual core processor. The travelled distance of the car is obtained by motion sensors from the electric motor. The ultrasonic sensors are connected by means of an Arduino Uno. A separate TAPAS three phase inverter board is used to drive the motors. A raspberry Pi 3 is used to communicate to the outside world. The FPGA controls the steering servo motors. In total five types of communication protocols are used in the system. A schematic layout of the car is shown in Figure2.3. Reference [9] claims better energy consumption than the vehicles which are used in [10].
CHAPTER 2. LITERATURE SURVEY
Figure 2.3: schematic layout of scaled car in [9]
An online project [12] describes a small robot, which uses an Arduino for processing. The robot is extended with a Raspberry Pi. The vehicle is shown in Figure2.4. It is stated that an Arduino is useful for interacting with sensors and motors. A Raspberry Pi on the other hand is useful to run computationally expensive algorithms like sensor fusion and image processing. Therefore the combination gives an inexpensive, but computationally powerful autonomous vehicle. The open source software library OpenCV is used for computer vision. Additionally ROS (robot operating system) is installed on the Raspberry Pi for development of robot applications.
CHAPTER 2. LITERATURE SURVEY
Figure 2.4: scaled vehicle which combines a Raspberry Pi and an Arduino [12]
The onboard computers used in [8], [9], [10] and [12] have been compared to the Olimex on-board computer used in the existing tractor semitrailer of TruckLab. The computing power of an external PC as used in TruckLab and in [8] exceeds the computing power of the onboard com-puters in terms of memory and processor speeds. ’The mini-ITX-board’ as used in [10] has the most computing power of the onboard computers. The dimension of 17 cm x 17 cm is however too large to fit inside the tractor of TruckLab. All the other onboard computers would fit. Next the Raspberry Pi as used in [9] and [12] has the most computing power. A Raspberry Pi is a computer which is able to run multiple programs simultaneously. The other onboard computers in descending computing power can only run one program at a time: The Zedboard used in [9], The Olimex as used in the existing tractor, the Arduino used in [9] and [12] and lastly the Atmega 162 microcontroller as used in cite [8]. The tractors of Trucklab should be able to perform multiple tasks at once, such as processing sensor data, controlling actuators and detecting obstacles. There-fore a Raspberry Pi is a suitable option to use for the new tractor of Trucklab instead of the Olimex.
From [9] and [12] it can be concluded that there are different ways in which hardware can be combined in order to reach the desired result. However, the system architecture can get quite complex. The improvement in terms of energy efficiency in [9] compared to [10] seems to result in added complexity. From this it can be learned that it is not the case that an improvement in one area, results in an overall better system. It is therefore important to identify what the exact problems are in the TruckLab and which ones should be addressed in order to reach the desired result. It should be decided which parts can be preserved from the original tractor semitrailers, which were not developed for research purposes. New hardware needs to be selected taking into account the effects it has on the complete functioning of the TruckLab system. From [12] it can be seen that adding a single board computer like a Raspberry Pi to the tractors from TruckLab would enable the use of additional software tools. This might be useful to further extend the capabilities of the TruckLab.