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Cogalloy L1 Advanced Mecanum ROS 2 Robot — Raspberry Pi 5 8 GB1 / 2
AdvancedSKU: COG-L1-ADV-MEC-8G

Cogalloy L1 Advanced Mecanum ROS 2 Robot — Raspberry Pi 5 8 GB

Cogalloy's advanced mobile-manipulation ROS 2 robot: Raspberry Pi 5 8 GB, Mecanum encoder drive, real-time control, 6-DOF arm and gripper, RGB-D depth vision, 2D dToF LiDAR and USB AI voice interaction.

  • Mobile manipulation in one system: Combine omnidirectional Mecanum motion with a 6-DOF arm and gripper for controlled perception-to-action experiments.
  • Raspberry Pi 5 8 GB + real-time control: Keep ROS 2 application compute and time-sensitive motor/encoder work in defined, inspectable layers.
  • Depth vision + 2D dToF LiDAR: Use complementary depth and planar-ranging data for perception, mapping, localization and navigation practice.
  • Voice with explicit safety boundaries: Use matched voice firmware as an application input after robot state and fallback behavior are defined.

Price

US$899.00

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Make sideways motion and arm reach part of one plan.

COGALLOY L1 ARCHITECTURE

Make sideways motion and arm reach part of one plan.

L1 Advanced Mecanum combines a holonomic base and articulated arm, which means a task can depend on both robot pose and end-effector pose. Start by proving individual base vectors, arm joints and cable clearance before planning a combined motion.

  • Four-wheel Mecanum motion for forward, lateral, diagonal and yaw movement
  • 6-DOF bus-servo arm and gripper for controlled manipulation experiments
  • Validate reach, balance and collision boundaries with the delivered build

OBSERVABLE CONTROL PATH

Separate high-level robotics from time-sensitive motion work.

The Raspberry Pi 5 8 GB host runs the operating system, ROS 2 and applications while the real-time control path handles motor, encoder and peripheral communication. That separation gives students and developers a clearer place to inspect commands, feedback and physical behavior.

  • Raspberry Pi OS, Ubuntu 22.04 LTS and ROS 2 Humble Docker reference environment
  • Confirm motor direction, encoder sign and low-speed Mecanum vectors before mapping
  • Record delivered firmware and wiring before changing controller parameters
Separate high-level robotics from time-sensitive motion work.
Validate each frame before joining vision, LiDAR and the arm.

PERCEPTION TO ACTION

Validate each frame before joining vision, LiDAR and the arm.

RGB-D vision, planar LiDAR and a manipulator are complementary but not automatically aligned. Check streams, timestamps, mounting and coordinate transforms before making a map, localizing in it or using a visual observation to trigger arm motion.

  • RGB-D depth camera for 3D perception and visual experiments
  • 2D dToF LiDAR for planar scan, mapping and navigation workflows
  • Verify camera-to-arm and arm-to-base transforms before a grasp task

SAFE LEARNING PROGRESSION

Combine autonomy only after the physical system is accepted.

A reliable progression is power and manual stop first; base motion and feedback next; sensors and transforms after that; then arm calibration, mapping, navigation and voice-driven behavior. Each layer should be repeatable before it is allowed to influence another one.

  • Keep a clear manual-stop path for every moving-robot test
  • Test voice intent with non-motion feedback before connecting it to robot behavior
  • Use the final packing list for configuration-specific accessories and power details
Combine autonomy only after the physical system is accepted.

Product details

Everything you need to evaluate the fit.

Clear product information, technical specifications and compatibility details—kept separate from the purchase decision.

Overview

Cogalloy L1 Advanced Mecanum — one ROS 2 platform for mobile manipulation

Cogalloy L1 Advanced Mecanum combines an omnidirectional encoder-motor base, Raspberry Pi 5 with 8 GB RAM, a dedicated real-time controller, a 6-DOF bus-servo arm and gripper, RGB-D depth vision, 2D dToF LiDAR and a USB AI voice interface. The configured system is intended for learning and prototyping across motion, perception, mapping, manipulation and human–robot interaction without treating those layers as isolated demos.

Start with a predictable mobile base

Four Mecanum wheels let the platform move longitudinally, laterally, diagonally and in yaw when wheel orientation, motor direction, encoder sign and kinematic parameters are correct. The high-level Raspberry Pi host and the real-time controller have distinct jobs: use the host for ROS 2 applications and use the controller path for time-sensitive motor, encoder and peripheral work. Validate low-speed vectors and odometry on the actual floor before relying on a map or a planned route.

Keep perception, manipulation and navigation in the same coordinate story

The Advanced configuration pairs an RGB-D depth camera with a planar 2D LiDAR. The camera supports depth-aware visual work; LiDAR supports planar scan, mapping and navigation workflows. The 6-DOF arm adds a physical action layer, so camera, arm and base transforms, cable clearance, reach limits and collision boundaries must be checked together. A usable autonomous task begins only after each sensor stream, transform and actuator path is repeatable on its own.

Voice is an application input, not motor authority

The included USB voice interface can provide wake-word and command input when it is used with the matched firmware and host software. Route recognised intents through explicit robot-state and safety checks. Network, account, cloud or large-model features depend on the selected software service and region; inclusion of voice hardware does not imply that every online feature is available offline or in every market.

Commission in layers before combining behavior

Charge with the matched charger, inspect battery polarity and establish a clear manual-stop path first. Then verify Mecanum motion, encoder feedback and controller communication; confirm depth-camera and LiDAR topics; calibrate arm neutral pose and low-speed joint motion; and finally test voice-driven non-motion feedback. Combine navigation, arm motion and voice only in a clear, level area after the physical envelope and fallback behavior are proven. The final order confirmation and packing list remain the source of truth for delivered accessory, sensor and regional-power revisions.

Technical specifications

Power

7.4 V 2200 mAh 10C protected battery configuration; runtime varies with workload, motion and network use

Storage

64 GB TF-card configuration

Mobility

Four-wheel Mecanum base with DC encoder motors for longitudinal, lateral, diagonal and yaw motion when correctly configured

Public SKU

COG-L1-ADV-MEC-8G

Compute host

Raspberry Pi 5, 8 GB RAM

Connectivity

Wi-Fi and Ethernet

Manipulation

6-DOF intelligent bus-servo arm with gripper

3D perception

Cogalloy Aurora930 Pro RGB-D depth camera

Configuration

Mecanum mobile base with Raspberry Pi 5 8 GB, arm, depth vision, 2D LiDAR and voice interface

Product class

Advanced ROS 2 mobile-manipulation robot

Product model

Cogalloy L1 Advanced Mecanum

Software stack

Raspberry Pi OS + Ubuntu 22.04 LTS + ROS 2 Humble Docker reference environment

Reference weight

Approx. 1.79 kg for the configured robot

Delivery boundary

Final packing list confirms the delivered sensor revision, accessories, charger and regional plug

AI voice interaction

Cogalloy Pro USB AI voice interaction module; matched firmware and host software required

Reference dimensions

212 × 174 × 441 mm for the configured robot

Commissioning boundary

Verify base kinematics, encoder feedback, sensor topics, transforms, arm calibration and manual-stop behavior before autonomous operation

Motion and I/O control

Cogalloy RRC Lite real-time robot controller

2D navigation perception

Cogalloy MS200 360° dToF 2D LiDAR

Shipping & support

Choose your destination at checkout to see the available shipping methods. Need integration advice before ordering? Our support team can help you choose compatible components.

In the box

Package contents

Cogalloy L1 Advanced Mecanum robot assembly

Configured Mecanum mobile base with integrated 6-DOF arm and gripper.

×1

Raspberry Pi 5 8 GB compute set

This configuration includes the 8 GB compute host, 64 GB TF-card configuration and matching host hardware.

×1 set

Motion-control and power set

Cogalloy RRC Lite control path, encoder-motor interfaces and protected 7.4 V battery configuration for the delivered robot.

×1 set

Depth and ranging perception set

Cogalloy Aurora930 Pro RGB-D depth camera and Cogalloy MS200 2D dToF LiDAR with their matched interfaces.

×1 set

AI voice interaction set

Cogalloy Pro USB voice hardware. Wake word, vocabulary and any cloud features depend on the matched firmware and host software.

×1 set

Final packing confirmation

Sensor revision, charger, regional plug, battery transport treatment and accessory details are confirmed by the final order and packing list.

Required check

Expert support

Frequently asked questions

What is COG-L1-ADV-MEC-8G?

It is the public Cogalloy SKU for L1 Advanced Mecanum with Raspberry Pi 5 8 GB. The configured robot combines Mecanum drive, a 6-DOF arm and gripper, RGB-D depth vision, 2D dToF LiDAR and USB AI voice hardware.

Does this configuration include the Raspberry Pi 5 and robotic arm?

Yes. COG-L1-ADV-MEC-8G is sold as the Raspberry Pi 5 8 GB mobile-manipulation configuration with the listed 6-DOF arm and gripper. The final order confirmation is the fulfillment record for each shipped item.

Can the Mecanum base move sideways?

Yes, when the four wheels are installed with the correct orientation and the controller has the matching Mecanum kinematics, motor direction and encoder sign. Test forward, lateral, diagonal and yaw vectors at low speed before autonomous use; slip and floor conditions affect odometry.

Which sensors are included?

The approved configuration includes a Cogalloy Aurora930 Pro RGB-D depth camera and Cogalloy MS200 2D dToF LiDAR. Confirm the final sensor and accessory revision on the order confirmation before an integration project begins.

Can it begin autonomous navigation and grasping immediately?

Only after controlled acceptance. Verify charging, battery polarity, base kinematics, controller/encoder feedback, sensor topics, coordinate transforms, arm neutral pose and collision limits first. Then validate mapping, localization, arm planning and combined behavior in a clear, level area.

What does the AI voice feature require?

The configuration includes the voice hardware. A working demonstration can also require the matched firmware, host software, network access, compatible account or cloud service. Route recognised intent through robot-state and safety checks, and keep an independent manual-stop path.

How should I commission the battery and motion system?

Use the matched charger before first use and confirm battery polarity before powering on. Check base movement, arm direction and sensor streams at low speed in a clear area, away from drops, people and loose cables. Follow the supplied battery guidance for charging and storage.

included

What's in the box