This project was built for a competition, to compete against similarly designed cars. It had to navigate a course, then pick up a half a pound weight carry it up a thirty degree incline.
Once at the top, the weight was set in a cup across a ten inch gap. The car then had to pick up another weight across the gap and transport it back down the incline and drop it off. The car had to then maneuver back through the course to the finish.
Overall, the car performed really well. The chassie was built using some sheet and angle aluminum. The drivetrain consisted of tank style steering. The drive servos chosen were tower pro mg995 because of metal gearing and high torque. Wheels for the car were designed in Creo and were 3D rapid prototyped. The main crane arm was also 3D rapid prototyped. Both the crane and stabilizing arm were made of carbon fiber. At the end of the crane fork there was a very small wire used to pick the weight up. The stabilizing arm was used to make sure the car didn't flip forward when the weight was being deposited or picked up from across the gap.
A Hitech 311 servo was fastened to the stabilizing arm. For the electronics and controls, a wireless Play Station 3 controller was chosen, that connected to a Bluetooth dongle. The dongle was then connected to the Arduino USB host shield, which was stacked on a regular Arduino UNO.
Once code was created, the driver servos and the stabilizer servo could be controlled directly from the ports of the Arduino USB Host shield. The crane was controlled by a Hitech mg485 servo that had been modified to be a DC motor. The motor was controlled by a two-channel relay board. The Arduino USB host shield sent a signal to the relay board to tell it when to send power to the motor, and in what direction.
After the car was designed, assembled, and some of the kinks were worked out, it was ready for competition. The car performed very well on the day of competition, posting the fastest time to complete the course. I would like to think my team members for their time and hard work (Darrin Small, Glen Smith, Lauren Toma, Alex Yoon, Dmytro Zaytsev, and Ximin Zhao).