youtube http://youtu.be/RC306Ex3aVU

Robot Ferda is modified kids electric car ("ride-on") for Robotour 2014. The main control system is Arduino based with ATmega2560. It takes care of motors control, integrates magnetometer and two sonars for obstacle detection. It also reads data from external GPS receiver via Bluetooth converter. Arduino software provides possibility to define GPS waypoints and the car tries to navigate by them. It can accept also commands from Bluetooth converter. The goal is to extend system with Android smartphone running simple application with visual navigation (to keep the robot on the road).

youtube http://youtu.be/ve-CoNReFTw

ARBot is a small robotic vehicle constructed for outdoor competitions of autonomous robots. The robot has four-wheels chassis, each wheel is powered and has encoder. Robot has camera, GPS, AHRS unit and three sonars. The computation is handled by DSP BF537 with power 1000 MIPS.

youtube https://www.youtube.com/watch?v=LBPyjKe679Y

The vehicle is driven by 36V DC motor and it can turn using an electric ram. It is controlled by the arduino microcontroller and additional computer.

youtube https://www.youtube.com/watch?v=BnWsfl_jUJA

Leopard Pro 36 converted to eletric power STM32F103 - motor/servo control, sensors Radxa Rock - navigation, optical recognition

youtube http://youtu.be/2H_66EUvTKg

Lot of hardware, lot of software, lot of fun.

All electronic of robot B-trix is, as in 2012, attached to electrochassis 1:5 and low-level control handles Arduino Duemilanove. There was serious upgrade of sensoric part - new laser rangefinder, compass has inclination compensation, number of sonar is tripled, "ordinary" camera was replaced by stereo camera. Xtion remained but nobody expects anything from it. GPS, magnetic encoder, gyroscopes and accelerometers are common sensors on this contest.

The high level control is managed by mini-ITX with Atom processor There are so many Ethernet toys that robot carries its own intranet. Software is mixture of Python, C++, C and bash. A plenty of vision, plenty of planning, but it is almost impossible to compute it in time.

youtube http://youtu.be/395K47_SHfc

The base of the robot is modified RC model TRAXXAS E-MAXX (3903). It is equipped with webcam, GPS, sonars HC-SR04, IMU with 3D compass and magnetic IRC. The basic sensors handles arduino mega. The image processing and GPS runs on 8" tablet with Intel Atom and Windows 8. The program is written in C++ and is using OpenCV.

youtube http://youtu.be/Doo27P37gCs

4 wheel drive powered by Lipo 42 5000 mAh motorcontroller: DRV8800 Controller: Beagle Bone Black

youtube http://youtu.be/FWOTWIGRihw

Robot Robík is own construction inspired by robot Orpheus. It weights approximately 15kg, driven by two DC motors with planetary gearbox. The wheels are connected with toothed belt. The control is own electronics based on ARM processor Cortex M3. Equipment: GPS + 9 DOF AHRS, sonar, camera+OpenCV on platform Odroid U3 for road detection.

youtube http://youtu.be/j4cK0xIAdUU

The robot construction is from freely available parts. The skeleton is mounted from aluminium profiles. The drive is by two electromotors with maximal combined power about 2.6 kW. The power supply is provided by two Pb accumulators 12V 72 Ah each (usually only one is used). The maximal speed is about 0.5 m/s. All modules (sensors, motor control, etc.) communicate by TCP/IP protocol.

Software is written in pure C++, and runs on older notebook. The road recognition uses neural networks. Park navigation may use GPS, maybe even some map.

youtube http://youtu.be/bAk96kyaTgc

Radioklub Písek is participating already for the 6th year on robotic outdoor competitions. Last year we completed new robot E-liška, and we took it for the first time to ROBOTOUR, where we reached 3rd place, again. And this year 3rd place on Robotem Rovně and 3rd place on RoboOrienteering . After small upgrades we count with it on ROBOTOUR 2014. E-liška dimensions are 95x60x48 cm and weight approximately 40 kg. The on-board voltage is 24V, provided by two gel accumulators 12V/18Ah. E-liška has spring-loaded four-wheel chassis with Ackermann steering and all wheels are powered. Each wheel has its own control unit. We use Lidar Sick , GPS a 9dof unit for orientation. The main control handles notebook, and motors have its own module with STM32. The power control is handled by H-bridges of own construction. The main program is written in Python and runs on Linux.

youtube https://www.youtube.com/watch?v=dAUn9LSuKm0

HARDWARE: Parallax (Motor Mount and Wheel Kit), encoders, 2xHB25 Sbot board (AVR ATmega128, designed and assembled by David Gustafik) PC ASUS UL30V 5x SRF-08 GPS NaviLock NL-302U USB SiRF III Compass with tilt compensation (HMC6343) AVR ATmega8 (compass driver) Camcorder Panasonic SDR-T50 (or USB webcam) video grabber EasyCap DC60 USB 2.0 TV DVD VHS Video Adapter W / Audio AV Capture TV DVD CVBS-Adapter usual usb hub Power: HAZE HZS 12V 9Ah handmade wood & aluminium base (contributions by Miroslav Nadhajský and Pavel Petrovič) red power switch, and power circuitry (contributions by Richard Balogh)

SOFTWARE: Ubuntu 14.04 Desktop LTS Netbeans OpenCV Smelý zajko controller utilizing an Artificial Neural Network (FANN) (result of Miroslav Nadhajský master thesis) SBOT firmware written in C/AVR Studio (David Gustafik) with modifications (Pavel Petrovič) Compass driver with serial port interface written in C/AVR Studio available at https://code.google.com/p/smely-zajko/

youtube https://www.youtube.com/watch?v=RYOczhVBujE

Robot's hardware was intended to be simple, modular reliable. It's main body is built from aluminium profiles. Motors are rigidly mounted with wheel mounted on their's shaft. Considering electronics, we use prebuild motor drivers, Discovery STM32F4 evaluation board with cape made by us, AHRS sensor, Hokuyo laser scanner, GPS receiver and nettop computer. All peripherials are conneted by USB link. Some parts, especially fixings, were 3D printed.

Software is composed of 3 main modules: localization, movement constraints and navigation. First one uses Extended Kalman Filter and data from AHRS, encoders and GPS to obtain global position. Second one uses Hokuyo laser scanner and camera to compute movement constraints. It consists two parts: obstacles detection from point cloud (agregated from laser scans) and terrain classification from combined camera image and point cloud intensity values. The last module uses Vector Field Histogram for local planning and A* for global one. As a base we use Ubuntu operating system. For telemetry and development purposes we use remote desktop and dedicated GUI.

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