Autonomous vehicles and mobility solutions for classroom and research
Autonomous vehicles are one of the most exciting emerging mobility solutions that is impacting both private mobility as well as public transit. Other significant areas where autonomous mobility has a significant role to play include transportation of goods and material, security, as well as surveillance among others.
According to some estimates, there will be over 20 million autonomous vehicles operational by 2030, creating more than 100,000 new jobs in U.S. alone during the next decade. It is therefore an urgent need to develop a talent pool that can contribute significantly in the development and research of these autonomous mobility solutions and fill this talent gap in the industry.
Autonomous Vehicles Research Studio :
This is the ideal solution for academics and researchers looking to build an indoor multi-vehicle lab in a short amount of time. Consisting of QDrone quadrotors and QBot 2e ground vehicles, ground control station, vision, and safety equipment, the Autonomous Vehicles Research Studio is the only option to jumpstart autonomous robotics academic and research programs and be productive in a very short amount of time.
The QDrone autonomous air vehicle is a midsize quadrotor equipped with a powerful onboard Intel® Aero Compute Board, multiple high-resolution cameras, and built-in Wi-Fi. As part of the Autonomous Vehicles Research Studio, this direct-access research-grade drone is tuned to accelerate your research and is ideal for innovative research in multi-agent, swarm, and vision-based applications.The durable, light-weight carbon-fiber frame makes the QDrone highly maneuverable and capable of withstanding high-impact applications with little downtime required for repairs. The powerful on-board processor, RGB-D and optical flow cameras enable high-quality on-board video processing, as well as streaming for real-time monitoring.
QBot 2e :
The QBot 2e is an innovative open-architecture autonomous ground robot, equipped with built-in sensors, and a vision system. Accompanied by extensive courseware, the QBot 2e is ideally suited for teaching undergraduate and advanced robotics and mechatronics courses, surpassing capabilities of hobby-level robotic platforms. The open-architecture control structure allows users to add other off-the-shelf sensors and customize the QBot 2e for their research needs.
The QBot 2e is built on a two-wheel differential drive platform with built-in DC motors and sensors. It utilizes a wireless embedded computer to command motor velocity and measure the onboard sensors including bump, cliff, and RGBD. The embedded system also provides several I/O channels for interfacing additional digital and analog sensors. The integrated RGB camera and depth sensorsare capable of capturing RGB image data and 11-bit depth data and transmitting the data at a high frame rate. The QBot 2e operates using a host-target structure. Controllers are developed on the ground station host using QUARC for Simulink®. Real-time code is downloaded from the host to the QBot 2e embedded computer and allows users to run, modify and monitor code remotely from the host. The controllers on-board the QBot 2e are open-architecture and fully modifiable.
LiDAR Steering SmartCar OSEK RTOS
This is an autonomous vehicle robot equipped with LiDAR sensor and steering system based on OSEK RTOS. You can learn about LiDAR sensor and other various sensors as well as self-driving, ROS and SLAM through this equipment.
LiDAR Steering SmartCar OSEK RTOS was created to support the research of ICT convergence service using intelligent mobile robot based on OSEK RTOS and the training of high value human resources. It combines data from acceleration, magnetic, and gyroscope sensors with vision, including 12 ultrasonic sensors and 8 infrared sensors. It can be used to develop innovative autonomous navigation algorithms and application services for mobile robots.
- Based on OSEK RTOS, 32 bit micro-controller is applied and about 20 practical exercise and programs are provided.
- Priority-based real-time scheduling function is included.
- Supports CAN network technology and Cortex-M4 core for internal communication of vehicles.
- Automobile robot with LiDAR sensor that includes collision avoidance exercise and location tracking exercise to learn about ROS and SLAM.
- By supporting the ADK-based electronic device development environment, the Google Smart Device Peripheral Design Platform, you can quickly and easily develop applications that work with Smart Devices with the Google Android platform.
- With 12 ultrasonic sensors and 8 infrared sensors, obstacles can be avoided and missions can be performed on a given route.
- DC geared motor has built-in encoder, so it can detect the operation status of motor and can calculate rotation direction and speed.
- Accurate steering control using servo motor is possible and it is able to change the rotation axis of front wheel for forward direction.
- Built-in Bluetooth communication module enables remote control based on SPP profile through PC, notebook, smartphone, tablet etc. that support Bluetooth communication.
- Smart phones and tablets can be used as the brain of mobile robots, enabling the implementation of mobile robot-based ICT convergence services using high-performance processors and Wi-Fi communication environments.
Drone with Lidar Sensor That You Can Control with GCS & GPS
- Drone Manufacturing and Control Using Open Platform
- Mission Flight Autofly Using GPS and GCS GPS(Global Positioning System) / GCS(Ground Control System)
- Drone flight and control (driver source code and flight mode source code provided)
- 4-propeller Quad Copter
- Learn how to assemble hardware and fly with open source
- Hovering function using LiDAR
- Drone flight using controller
- Support Ground Control System capable of drone control on Windows or Android OS
- Support auto-flight using GPS and Ground Control System configured in drone
- Mission planning function : Waypoint routing, event execution
(Go to designated place and carry out mission (photographing, collecting geographic information, etc.))
- Drone Intro : Definition / Type / Configuration / Principles of Operation / Frame Selection / Flight Controller Selection / Ground Station Selection / Hardware, Firmware, Software Preparation / Additional Hardware / Safety Precautions
- Drone Manufacturing : Hardware Assembly / Mission Planner Installation / Firmware Programming / Connecting Mission Planner and Ardupilot / Hardware Set-up
- Flight : Flight Mode Set-up / Safety Inspection Before Motor Operation / Start & Stop Motor / Tips for Beginners / Basic Tuning / Measuring Vibration / Hovering Set-up / Trimming Set-up / Safety Device / Pre-Flight Checklist
- Advanced Set-up : Auto Tune / Auxiliary Function / Gyro Calibration / Battery Power Limit Set-up / EKF / Flight Time Record / Take-off & Landing Control Set-up / Motor Scaling Ratio Set-up / Offset Compensation Set-up for Sensor Location / Sensor Check / Remote Port Configuration / Tuning
- Flight Controller and Source : Flight Controller Hardware / Source Code
- GCS-Mission Planner : Mission Planning through Waypoint and Event / Mission Command List / Application
- GCS-QGROUND CONTROL : Intro / Download and Install App / Menu / Planning / Set-up / Flight / Application
- LogData : Diagnose problems using Log Data / Analyze Dataflash Log Data / Remote Communication Log Data / Save and Execute Log Data
- Others : FPV / Indoor Flight Guide / Multi-Flight / Antenna Tracking / Simulation / Reference
Autonomous vehicles are coming and it is important to prepare for them, and to prepare a generation of engineers and researchers to work on these exciting technologies that will drive our future.