Roboworks Pickerbot Mini
- SKU: MBS-ROB-96
- GTIN: 0658917504939
- Category: Research & Education
Roboworks Pickerbot Mini
- Jetson Orin Nano 4GB
- ROS computer
- 3-axis robotic arm with soft gripper
Description
The Pickerbot Mini is a mobile pick-and-drop robot based on ROS (Robot Operating System) – designed for researchers, developers, educators, students and ambitious hobbyists. It combines a mobile mecanum platform with a robot arm and extensive sensors into a ready-to-use learning and development platform.
The Pickerbot Mini is equipped with a built-in ROS computer, a 3-axis robot arm with soft gripper, LiDAR and depth camera, an STM32 controller for motor, power supply and IMU, as well as a metal chassis with omnidirectional mecanum wheels. ROS and Ubuntu come pre-installed including all essential packages and drivers – so the platform is ready to go within minutes.
Thanks to its compact design and affordable entry price, the Pickerbot Mini is ideal for ROS beginners and equally suited as a prototyping platform for research and development projects. Comprehensive classroom materials (manual, tutorials, sample code) make it easy to integrate into the curriculum; the system is expandable with accessories such as voice recognition modules, LCD display or external keyboard.
Technical specifications
| ROS computer | NVIDIA Jetson Orin Nano or Orin NX (selectable) |
| Robot arm | 3-axis arm with soft gripper |
| Sensors | LiDAR, depth camera |
| Controller | STM32 (motor / power supply / IMU) |
| Chassis / drive | metal chassis with omnidirectional mecanum wheels |
| Software | ROS + Ubuntu pre-installed (incl. packages & drivers) |
| Expandability | voice recognition, LCD display, external keyboard and more |
Technical specifications
Platform & mechanics
| Dimensions (chassis + arm reach) | 460 × 533 × 516 mm (L × W × H) |
| Weight | 12.6 kg |
| Payload | 15 kg |
| Drive | omnidirectional mecanum wheels (2WD or 4WD, model-dependent) |
| Wheel diameter | 100 mm |
| Max. speed | 2.33 m/s |
| Drive motor | MD36L DC brushed motor, 60 W, 1:27 reduction |
| Encoder | 500-line GMR AB-phase encoder (high-precision) |
| Suspension | model-dependent (standard model without independent suspension) |
Computing & controllers
| ROS computer | NVIDIA Jetson Orin Nano or Orin NX (selectable) |
| Microcontroller | STM32F103RC (ARM Cortex-M3, 72 MHz, 512 KB flash, 64 KB SRAM) – motor control, power management, IMU |
| I/O interfaces | CAN, serial ports, USB, HDMI |
Arm & gripper
| Robot arm | 3-axis parallel manipulator (metal), single base motor |
| Gripper | two-finger soft gripper |
| Gripper camera | RGB camera (mounted above the gripper) |
Sensors
| LiDAR | Leishen LSLiDAR M10P – 360°, range 30 m, scan frequency 12 Hz |
| Depth camera | Orbbec Astra (depth image / point cloud) |
| RGB camera | at the gripper |
Power supply
| Battery | „Power Mag" – 22.4 V LFP (LiFePO₄), 6000 mAh, magnetic metal housing |
| Runtime | 6.5 h without load / 5.5 h with 3 kg load |
| Charger / connectors | 3 A DC; charging DC4017MM, discharging XT60U-F |
| Discharge current / protection | 15 A continuous; protection against short circuit, overcurrent, overcharge, over-discharge; charging while in use possible |
| Optional battery | 22.4 V, 20,000 mAh (20 A continuous, 4.1 kg) |
Control & software
| Remote control | wireless remote controller; iOS/Android app (WiFi/Bluetooth); ROS 2 node + keyboard or USB controller |
| Software | ROS 2 Humble pre-installed; MiROS cloud visual programming |
Functions & ROS packages
Computer vision
OpenCV, KCF tracking, AR marker recognition, RGB line following, skeleton tracking, 3D object recognition, ORB mapping
SLAM & navigation
Obstacle avoidance, RTAB visual mapping, RTAB visual + LiDAR mapping, Gmapping, Hector, Karto, Cartographer (incl. 3D reconstruction), RRT path planning, LIO-SAM and LeGO-LOAM 3D reconstruction
Deep learning
YOLO object, gesture and traffic sign recognition, model training, gesture control, TensorFlow object recognition/detection, handwritten digit recognition
Scope of delivery
- 1× Pickerbot Mini, ready to use, with ROS computer
- pre-installed ROS + Ubuntu image
- classroom materials: user manual, tutorials and ROS sample code
| Item information | Value |
|---|---|
| Shipping weight: | 15,00 kg |
| Item weight: | 12,60 kg |
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