Robotics Kits

Image Part Number Description / PDF Quantity Rfq
27315

27315

Parallax, Inc.

KIT ROBOT PENGUIN NICKL ANODIZED

0

EKT-EVALBOT

EKT-EVALBOT

Texas Instruments

KIT EVLBOT CODERED TECH LM3S9B92

0

28190

28190

Parallax, Inc.

DAGU ROVER 5 TRACKED W/ENCODERS

0

110060487

110060487

Seeed

QUIRKBOT ROBOTIC CREATURES KIT

0

240-049

240-049

Digilent, Inc.

ROBOTICS LINE ACCESSORY KIT

0

110090037

110090037

Seeed

UARM VACUUM GRIPPER SYSTEM KIT

0

28202

28202

Parallax, Inc.

KIT GRIPPER FOR BOE-BOT

0

240-048

240-048

Digilent, Inc.

KIT MOTOR ROBOT MRK

0

80090

80090

Parallax, Inc.

ELEV-8 AIRFRAME & HARDWARE KIT

0

114990171

114990171

Seeed

ROBOT GRIPPER

0

28136

28136

Parallax, Inc.

KIT SCRIBBLER ROBOT

0

1529

1529

Adafruit

HEXY PROGRAMMABLE HEXAPOD KIT

0

R500

R500

Global Specialties

ROBOTIC CATERPILLAR

0

910-90005

910-90005

Parallax, Inc.

KIT BASIC STAMP-PORTABLE DEVICE

0

RP6V2-C

RP6V2-C

Global Specialties

RP6V2 ROBOTIC VEHICLE TANK

0

28336

28336

Parallax, Inc.

KIT SCRIBBLER 2 ROBOT

0

95026

95026

Makeblock

9G MICRO SERVO PACK

0

27313

27313

Parallax, Inc.

KIT ROBOT PENGUIN RED ANODIZED

0

28985

28985

Parallax, Inc.

KIT FOR STINGRAY - PING

0

K036

K036

M5Stack

ROVERC (W/O M5STICKC)

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
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