Robotics Kits

Part Number	Description / PDF	Quantity
PIS-0241 Pi Supply	CAMJAM EDUKIT 3 ROBOTICS	0
903-0256-300 ROBOTIS	FR12-G101GM GRIPPER SET	18
110090267 Seeed	TS100 SHOCK ABSORBER TANK CHASSI	0
RDMK1901 Rotrics	ROTRICS MAKER KIT	50
110090144 Seeed	ALPHABOT WHEELED FOR ARDUINO	0
902-0113-000 ROBOTIS	CM-15 CONTROLLER	10
PIS-1585 Pi Supply	BIT:BUGGY CAR W/O MICRO:BIT	47
110090181 Seeed	QSCOUT ROBOT BUILDING KIT LINE F	0
PIS-0938 Pi Supply	YETIBORG V2 4WD ROBOT KIT	5
KIT-16417 SparkFun	JETBOT AI KIT V2.1 POWERED BY JE	0
110090221 Seeed	SEEEDSTUDIO JETBOT SMART CAR POW	0
ROB0081 DFRobot	MINIQ 2WD ROBOT KIT V2.0 (ARDUIN	0
ROB0111 DFRobot	MINIQ 4WD CROSS COUNTRY ARDUINO	0
101990640 Seeed	MU VISION SENSOR 3 - AI ROBOT VI	0
114090055 Seeed	MINI REMOTE CONTROL TOY CAR BLUE	0
KIT0085 DFRobot	RUBBER WHEEL & MOTOR KIT	0
ROB0112 DFRobot	DEVASTATOR TANK MOBILE ROBOT PLA	0
902-0062-000 ROBOTIS	CM-530 CONTROLLER	9
80200 Parallax, Inc.	ELEV-8 QUADCOPTER KIT V2	0
P1040007 Makeblock	AIRBLOCK BATTERY	0

Robotics Kits

1. Overview

Maker/DIY educational robotics kits are modular platforms designed to teach robotics, programming, and engineering concepts through hands-on assembly and experimentation. These kits combine hardware components (sensors, actuators, microcontrollers) with software tools (IDEs, libraries) to enable learners to build functional robots. Their importance lies in fostering STEM (Science, Technology, Engineering, Mathematics) skills, computational thinking, and problem-solving abilities in educational and hobbyist environments.

2. Main Types and Functional Classification

Type	Functional Features	Application Examples
Entry-Level Kits	Pre-assembled modules, visual programming (Scratch/Blockly), basic sensors	K-12 classrooms, coding camps
Programming-Focused Kits	Support for Python/C++, advanced AI/ML libraries, ROS integration	University labs, robotics competitions
Mechanical Arm Kits	6-DOF articulated joints, precision control, CAD design tools	Industrial automation training, mechatronics courses
Autonomous Navigation Kits	LIDAR, SLAM algorithms, computer vision modules	Self-driving car prototypes, drone development

3. Structure and Components

Typical robotics kits consist of:

Mechanical Structure: Aluminum/plastic frames, gears, wheels, and linkage systems
Electronic Components: Microcontrollers (Arduino/Raspberry Pi), motor drivers, power management modules
Sensors: Ultrasonic, IR, IMU (Inertial Measurement Units), vision cameras
Actuators: Servos, DC motors with encoders, stepper motors
Software: Cross-platform IDEs, simulation tools (Gazebo), firmware libraries

4. Key Technical Specifications

Parameter	Importance
Processor Architecture	Determines computational capability (e.g., ARM Cortex-M7 for real-time processing)
Sensor Compatibility	Dictates environmental interaction capabilities
Programming Language Support	Affects learning curve and project complexity (Python vs. C++)
Expansion Interfaces	GPIO, I2C, UART for adding custom peripherals
Battery Life	Critical for mobile/autonomous applications

5. Application Areas

Primary application sectors include:

Education: Classroom robotics labs, competition platforms (FIRST Robotics)
Research: Prototyping for academic studies in AI/robotics
Industrial Training: Automation system simulations
Healthcare: Assistive robot prototypes for therapy applications
Entertainment: Interactive installations and hobbyist projects

6. Leading Manufacturers and Products

Manufacturer	Representative Product	Key Features
LEGO Education	Spike Prime	Modular brick-based system with Scratch programming
Makeblock	Ultimate 2.0	ROS-supported mechanical arm with Python API
Arduino	Arduino Robot Kit	C++ programming environment with sensor integration
UBTech	Walker	Humanoid robot with AI vision and motion algorithms
DJI	RoboMaster EP	SDK-enabled drone with computer vision capabilities

7. Selection Recommendations

Key consideration factors:

User skill level (beginner vs. advanced)
Educational objectives (coding vs. mechanical engineering focus)
Budget constraints ($50-$500 range typical)
Expansion potential (modular vs. fixed architecture)
Software ecosystem maturity (community support, documentation quality)

8. Industry Trends Analysis

Emerging trends include:

Integration with AI/ML frameworks (TensorFlow Lite, OpenCV)
Cloud-connected robotics via IoT platforms
Standardization of educational curricula (NGSS, Common Core)
Increased use of simulation environments (Webots, ROS Gazebo)
Growing emphasis on collaborative robots (cobots) for classroom safety