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Bring your lessons to life with virtual reality. Spark curiosity and engage the entire classroom with the RobotLAB VR classroom pack
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The Dobot Magician Mini Car Assembly Line is a compact, benchtop automation training cell that RobotLAB supplies for classrooms and CTE labs. It combines a 4-axis Dobot Magician robotic arm with a speed-adjustable conveyor belt, photoelectric sensors, fixtures, and a parts kit so learners can stage, move, assemble, and inspect parts in repeatable sequences β the same material-flow logic used on a real automotive line, shrunk to a single desk.
Students start by building programs visually in Blockly, then progress to Python for timing, data handling, and conditional logic. Because the cell coordinates the arm with conveyor detection and indexing, it teaches the concepts that matter most in modern manufacturing: sensing a part's arrival, triggering a pick, sequencing stations, and verifying the result. The modular fixtures let an instructor reconfigure stations for different lessons, team rotations, and increasing skill levels without special infrastructure.
RobotLAB sells, deploys, trains on, and supports this kit nationwide as part of its Dobot education lineup. The footprint fits standard lab benches and shared classrooms, and RobotLAB provides curriculum-aligned onboarding and US-based service so a teacher can run a full automation unit out of the box. To confirm the exact bill of materials, lead time, and any volume or RaaS options for your program, call 1-87-RobotLAB.
| Robot model | Dobot Magician (4-axis desktop arm) |
| Number of axes | 4 |
| Arm payload | 500 g |
| Maximum reach | 320 mm |
| Position repeatability | 0.2 mm |
| Conveyor effective length | 600 mm |
| Conveyor max speed | 120 mm/s |
| Conveyor payload | 500 g |
| Sensors | Photoelectric sensors, limit switches |
| Programming | Blockly (visual) and Python |
| Arm communication | USB, Wi-Fi, Bluetooth |
| Power supply | 100β240 V, 50/60 Hz |
| Configuration | Stationary desktop training cell; modular fixtures |
| Included | Magician arm, conveyor kit w/ sensors, fixtures & mounts, parts kit, cables, example programs, quick-start materials |
| Purchase Price | $1,599 |
Career and technical education programs use the cell to give students hands-on time with the exact skills employers want: programming a robot to pick from a moving conveyor, sequencing stations, and using sensors to gate each step. Because it mirrors real assembly-line flow on a desktop, learners build job-ready automation and PLC-style logic without a full industrial cell. RobotLAB can bundle curriculum and instructor training so a workforce program is teaching automation the first week.
Middle and high school robotics classes use Blockly to introduce the arm-and-conveyor system, then graduate motivated students to Python. The compact, self-contained footprint fits a standard classroom bench and needs no special power or air, so a single teacher can run rotations across small teams. It turns abstract "smart factory" ideas into a tangible machine students can program and debug.
University manufacturing, mechatronics, and industrial-engineering labs use the cell as an affordable platform for process-optimization, throughput, and material-flow experiments. Students can model station timing, test pick strategies, and study how sensing affects cycle time β then iterate in Python. It complements larger industrial arms by giving every student bench-level access instead of waiting for one shared cell.
Same-day response. We handle delivery, on-site setup, staff training, and ongoing service nationwide.
As listed by RobotLAB, the kit includes a Dobot Magician robotic arm, a conveyor belt kit with sensors, fixtures and mounts, a parts kit, power and connection cables, example programs, and quick-start materials. It is a single-cell desktop training system rather than a multi-arm factory. For a written, itemized bill of materials before you order, call 1-87-RobotLAB.
It is an educational training cell. It reproduces real assembly-line concepts β conveyor flow, part detection, indexing, pick-and-place, and station sequencing β on a desktop so students learn industrial automation logic. It is not intended for production manufacturing output.
Learners begin with Blockly, a drag-and-drop visual environment, then move up to Python for timing, data, and conditional logic. This progression lets the same cell serve beginners and advanced students. RobotLAB can recommend curriculum that matches your grade band β call 1-87-RobotLAB.
Yes. RobotLAB describes it as a compact footprint that fits standard lab benches and shared classrooms without special infrastructure, running on standard 100β240 V power. No compressed air or dedicated electrical service is required for the base cell.
The standalone Magician is a single arm. This kit adds the conveyor, sensors, fixtures, parts, and example programs needed to teach material flow and multi-station sequencing β the assembly-line dimension the bare arm can't demonstrate. If you only need the arm, RobotLAB also sells the Magician V3 Standard and Advanced Educational Plan; call 1-87-RobotLAB to compare.
Yes. RobotLAB sells, deploys, trains, and services Dobot education products nationwide with US-based support, and can provide instructor onboarding and curriculum alignment. We can also discuss multi-unit pricing for full classrooms and lease or RaaS options. Call 1-87-RobotLAB to scope your program.
It is a single-arm, single-conveyor station, so it is best run in small-team rotations β a typical setup is two to four students per cell working through lessons together. For full-class coverage, programs often buy multiple cells; call 1-87-RobotLAB for a per-seat recommendation and volume pricing.

Bring your lessons to life with virtual reality. Spark curiosity and engage the entire classroom with the RobotLAB VR classroom pack

RobotLAB NAO Classroom Pack

The 25-degree-of-freedom bipedal humanoid trusted by Yale, MIT, Stanford and 400+ universities for hands-on robotics, AI and human-interaction teaching β delivered, trained and supported by RobotLAB.
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