ROSKY Smart Mobile Platform Discontinued

What this kit teaches

Course outline

01 Robot Operating System installation guide (3 class periods)

Unit content

• Introduction to ROS
• Preparing before installation
• Installing the VirtualBox virtual machine
• Installing and configuring Ubuntu
• Installing tool packages
• Installing and testing ROS

Matching materials: “ROSKY Smart Mobile Platform User Manual” (Jetson Nano edition), Chapter 1, 24 pages

02 Turtlesim guide (4 class periods)

Unit content

• Before you start
• Learning basic ROS operations with Turtlesim

Matching materials: “ROSKY Smart Mobile Platform User Manual” (Jetson Nano edition), Chapter 2, 27 pages

03 Using ROSKY and setting up the environment (2 class periods)

Unit content

• ROSKY hardware configuration
• Remote operation setup

Matching materials: “ROSKY Smart Mobile Platform User Manual” (Jetson Nano edition), Chapter 3, 16 pages

04 ROSKY remote control and path calibration (2 class periods)

Unit content

• Remote login
• Controlling ROSKY remotely
• Calibrating ROSKY’s movement path

Matching materials: “ROSKY Smart Mobile Platform User Manual” (Jetson Nano edition), Chapter 4, 11 pages

05 ROSKY SLAM and navigation (3 class periods)

Unit content

• Introduction to the TF coordinate system
• Remote login methods
• How to use the LiDAR
• Controlling ROSKY remotely
• Simultaneous localization and mapping (SLAM)
• Navigating with a static map

Matching materials: “ROSKY Smart Mobile Platform User Manual” (Jetson Nano edition), Chapter 5, 20 pages

06 ROSKY lane following (2 class periods)

Unit content

• Remote login and video streaming
• Camera intrinsic parameter calibration
• Camera extrinsic parameter calibration
• Camera HSV parameter tuning
• Lane following

Matching materials: “ROSKY Smart Mobile Platform User Manual” (Jetson Nano edition), Chapter 6, 13 pages

07 Competition case study (2 class periods)

Unit content

• ROSKY competition example “Timed Rescue Challenge”
• Setting up the environment
• Building a static map
• Navigating to a specified location
• Navigating with different algorithms
• 2020 ROS Summer School

Matching materials: “ROSKY Smart Mobile Platform User Manual” (Jetson Nano edition), Chapter 7, 14 pages

The course outline is based on the CIRCUS Pi teaching manual. Class period counts are estimates and can be adjusted to fit your class.

Hardware specifications

Single-board computer	NVIDIA Jetson Nano Developer Kit (2nd generation)
GPU	128-core NVIDIA Maxwell™
CPU	Quad-core ARM A57 @ 1.43 GHz
Memory	4 GB 64-bit LPDDR4 25.6 GB/s
Storage	microSD (card not included)
Video decoder	4Kp60 | 2x 4Kp30 | 8x 1080p30 | 18x 720p30 (H.264/H.265)
Connectivity	Gigabit Ethernet, M.2 Key E
Camera	2x MIPI CSI-2 connectors
Display	HDMI and DP
USB	4x USB 3.0, 1x USB 2.0 Micro-B
Other	‧ 40-pin header (GPIO, I2C, I2S, SPI, UART) ‧ 12-pin header (power and related signals, UART) ‧ 4-pin fan header
Mechanical specifications	100 mm x 80 mm x 29 mm
Operating system	Ubuntu 18.04.3 LTS + ROS Melodic
Camera lens	‧ Resolution 3280*2464 ‧ Size 25*24 mm ‧ Camera parameters ‧ CMOS 1/4 inch ‧ Aperture (F) 2.35 ‧ Focal length 3.15 mm ‧ FOV 160 degrees ‧ Distortion <14.3%
LiDAR	‧ Scan frequency 6 Hz~12 Hz ‧ Ranging distance <10 m ‧ Ranging frequency up to 5 kHz
Motors	Metal gear motors (with encoders) ×4, rated voltage 6 V, torque 1.5 N.m, gear ratio 1:90
Motor controller board	‧ USB / TTL (UART) ‧ Input voltage: 10.8 V~16 V ‧ Controls 4 motors, encoder-equipped or standard DC ‧ 6-axis accelerometer ‧ 12 V/2 A power output port ×1 ‧ 5 V/4 A power output port ×3 ‧ 3.3 V/2 A power output port ×1
Chassis	Aluminum alloy chassis (quick-release magnetic latch base plate)
Accessories	‧ Cat 5e Ethernet cable ‧ Intel8265AC wireless card (includes 20 cm cable and antenna) ‧ Precision hex key set (7 pieces) ‧ HDMI female to VGA male adapter cable ‧ 12.6 V 2 A lithium battery charger ‧ 18650 lithium battery 3400 mAh ×3
Vehicle dimensions	About 200 x 210 x 160 mm (LxWxH)
Box dimensions	About 384 x 276 x 208 mm (LxWxH)

Features

The ROSKY series of smart mobile platforms was a selected teaching material for the 2020–2021 “Taoyuan ROS Summer School Robotics Summer Course.” It is a teaching kit well suited to ROS learners. It is the version compatible with ROS Summer School and uses a Jetson Nano as its main board.

• NVIDIA Jetson Nano (with a GPU for AI neural network workloads)
• Supports ROS/ROS2 development
• IMX219-160 camera (8 megapixels, 160-degree wide angle)
• YDLIDAR-X4 laser rangefinder
• Aluminum alloy chassis with a quick-release magnetic latch bottom cover and four-wheel drive
• Custom-designed motor controller board (offers multiple power outputs, a power slot for three 18650 lithium batteries, battery level monitoring, and a six-axis sensor)

System architecture

Feature overview

Learning manual

Training events
2020 Taoyuan ROS Summer School Robotics Summer Course
2021 Taoyuan ROS Summer School Robotics Summer Course

Videos