Release
Jan 1, 2018
Price
Price TBA
Connectivity
3
Status
Active
Height
58cm
Weight
5.6kg
Battery
~60–90 minutes
NAO6
The sixth generation of the iconic NAO humanoid robot, originally developed by Aldebaran Robotics (France) and now manufactured by Maxtronics after Maxvision Technologies acquired Aldebaran's assets in 2025. Standing 58cm tall with 25 degrees of freedom, NAO is one of the most widely deployed humanoid robots in history — over 13,000 units in use across 70+ countries. NAO replaced Sony's AIBO as the RoboCup Standard Platform League robot in 2007 and has been used in education, research, healthcare, and autism therapy. Features multilingual speech, facial recognition, and the Choregraphe graphical programming tool. Development began as 'Project Nao' in 2004.
Listed price
Price TBA
Contact sales (educational/research pricing)
Release window
Jan 1, 2018
Current status
Active
Aldebaran / Maxtronics
Last verified
Mar 26, 2026
Technical overview
Core specifications and system stack
A fast read on the mechanical profile, sensing package, and platform integrations behind NAO6.
Technical Specifications
Height
58cm
Weight
5.6kg
Battery Life
~60–90 minutes
Charging Time
~2 hours
Max Speed
Not disclosed
Tech Components
Sensors (7)
Connectivity (3)
Voice Assistants
Operational profile
How this robot is configured
Capabilities
11
Connectivity
3
Key capabilities
Ecosystem fit
Certifications
Explore further
Benchmark set
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About the NAO6
The NAO6 is a Research robot built by Aldebaran / Maxtronics. The sixth generation of the iconic NAO humanoid robot, originally developed by Aldebaran Robotics (France) and now manufactured by Maxtronics after Maxvision Technologies acquired Aldebaran's assets in 2025. Standing 58cm tall with 25 degrees of freedom, NAO is one of the most widely deployed humanoid robots in history — over 13,000 units in use across 70+ countries. NAO replaced Sony's AIBO as the RoboCup Standard Platform League robot in 2007 and has been used in education, research, healthcare, and autism therapy. Features multilingual speech, facial recognition, and the Choregraphe graphical programming tool. Development began as 'Project Nao' in 2004.
Pricing has not been publicly disclosed. See all Aldebaran / Maxtronics robots on the Aldebaran / Maxtronics page.
Spec Breakdown
Detailed specifications for the NAO6
Height
58cmAt 58cm, the NAO6 is sized for its intended operating environment and use cases.
Weight
5.6kgWeighing 5.6kg, the NAO6 balances structural integrity with portability and maneuverability.
Battery Life
~60–90 minutesWith a battery life of ~60–90 minutes, the NAO6 can operate for sustained periods before requiring a recharge. Battery life is measured under typical operating conditions and may vary based on workload intensity and environmental factors.
Charging Time
~2 hoursA charging time of ~2 hours means the ratio of operation to downtime is an important consideration for applications requiring near-continuous availability. Some deployments use multiple robots in rotation to maintain uninterrupted service.
The NAO6 uses Intel Atom E3845 quad-core CPU, NAOqi OS (Linux-based) as its intelligence backbone. This AI platform powers the robot's decision-making, perception processing, and autonomous behavior. The sophistication of the AI stack directly impacts how well the robot handles unexpected situations and adapts to new environments.
NAO6 Sensor Suite
The NAO6 integrates 7 sensor types, forming the perceptual foundation that enables autonomous operation.
This sensor configuration enables the NAO6 to perceive its environment and operate autonomously in its intended use cases. Multiple sensor modalities provide redundancy and more robust perception than any single sensor type alone.
Explore sensor technologies: components glossary · full components directory
NAO6 Use Cases & Applications
Research robots serve as platforms for advancing robotics science and engineering. They enable researchers to test theories about locomotion, manipulation, perception, and human-robot interaction in controlled and real-world environments.
Capabilities That Enable Real-World Use
The NAO6 offers 11 distinct capabilities, each contributing to the robot's practical utility.
These capabilities work together with the robot's 7 onboard sensor types and Intel Atom E3845 quad-core CPU, NAOqi OS (Linux-based) AI platform to deliver practical, real-world performance.
Ecosystem Integration
The NAO6 integrates with the following platforms and ecosystems, extending its utility beyond standalone operation.
This ecosystem compatibility enables the NAO6 to work as part of a broader automation setup rather than operating in isolation.
NAO6 Capabilities
11
Capabilities
7
Sensor Types
AI
Intel Atom E3845 quad-core C…
Autonomous Navigation
Autonomous navigation allows the NAO6 to move through its environment without human guidance, planning efficient paths around obstacles and adapting to changes in real time. For a research robot, this involves simultaneous localization and mapping (SLAM) to build and maintain environmental models, path planning algorithms to find efficient routes, and reactive obstacle avoidance for unexpected situations. The complexity of autonomous navigation scales dramatically with the environment — navigating a structured warehouse is substantially different from navigating a cluttered home or outdoor space. The NAO6's navigation system must handle the specific challenges of its intended deployment scenarios reliably and repeatedly.
Additional Capabilities
Connectivity & Integration
How the NAO6 communicates with your network, smart home devices, cloud services, and companion apps.
Network & Communication Protocols
Voice Assistant Integration
NAO6 Technology Stack Overview
The NAO6 by Aldebaran / Maxtronics integrates 12 distinct technology components across sensing, connectivity, intelligence, and interaction layers. The physical platform features a height of 58cm, a weight of 5.6kg, providing the foundation on which this technology stack operates.
Perception — 7 Sensor Types
The perception layer is built on 2 HD Cameras (forehead + mouth), 4 Directional Microphones, 2 Ultrasonic Sensors, Inertial Measurement Unit, 8 Force-Sensing Resistors (feet), 2 Bumpers (feet), Tactile Sensors (head, hands). These work in concert to give the robot a detailed understanding of its operating environment. This multi-sensor approach provides redundancy and enables the robot to function reliably even when individual sensors encounter challenging conditions such as low light, reflective surfaces, or cluttered spaces.
Connectivity — 3 Protocols
For communications, the NAO6 relies on Wi-Fi (802.11a/b/g/n), Ethernet, Bluetooth 4.0 (LE). This connectivity stack ensures the robot can communicate with cloud services, local smart home devices, mobile apps, and other networked systems in its environment.
Intelligence — Intel Atom E3845 quad-core CPU, NAOqi OS (Linux-based)
Intel Atom E3845 quad-core CPU, NAOqi OS (Linux-based) serves as the computational brain, processing sensor data, making navigation decisions, and orchestrating the robot's autonomous behaviors. The quality of this AI platform directly influences how well the robot handles novel situations, adapts to changes in its environment, and improves its performance over time through learning.
Voice — Multilingual Text-to-Speech (2 speakers)
Voice interaction is handled through Multilingual Text-to-Speech (2 speakers), providing natural language understanding and speech synthesis that enable conversational control and integration with broader smart home ecosystems.
Who Should Consider the NAO6?
Target Audience
Research robots are acquired by universities, government labs, and corporate R&D departments. They serve as experimental platforms for developing new algorithms, testing locomotion strategies, and advancing the field of robotics. Some are also used for educational purposes.
Key Considerations
Open-source software compatibility (ROS/ROS 2), sensor modularity, programmability, available SDK/API quality, community support, and published research papers using the platform are key factors. Documentation quality and the ability to modify both hardware and software are essential for research use.
Pricing
Availability
ActiveThe NAO6 has a status of Active. Check with Aldebaran / Maxtronics for the latest availability details.
NAO6: Strengths & Trade-offs
Engineering compromises and where this research robot excels
What the NAO6 does well
Extensive sensor suite
With 7 sensor types onboard, the NAO6 has one of the more comprehensive perception systems in the research category. This multi-modal approach enables robust environmental awareness, redundant obstacle detection, and reliable autonomous operation even in challenging conditions. More sensor diversity generally translates to better real-world adaptability.
Broad capability set
With 11 distinct capabilities, the NAO6 is designed as a versatile platform rather than a single-task device. This breadth means the robot can handle varied scenarios and workflows, reducing the need for multiple specialized robots and increasing its utility across different situations.
What to consider carefully
Limited battery runtime
A battery life of ~60–90 minutes means shorter operational windows between charges. For applications requiring continuous or extended operation, this may necessitate scheduling around charge cycles or deploying multiple units in rotation. Evaluate whether the runtime meets your minimum session requirements before committing.
Charging time exceeds runtime
With a charging time of ~2 hours compared to a battery life of ~60–90 minutes, the NAO6 spends more time charging than operating. This ratio is common in high-performance robotics but is an important factor for planning continuous-availability deployments.
Undisclosed pricing
Aldebaran / Maxtronics has not published a public price for the NAO6. While common for enterprise-class robotics, the absence of transparent pricing can complicate budgeting and comparison shopping. Prospective buyers will need to engage directly with the manufacturer for quotes, which may vary by configuration and volume.
Note: This strengths and trade-offs assessment is based on the NAO6's documented specifications as tracked in the ui44 database. Real-world performance depends on deployment conditions, firmware maturity, and environmental factors. For the most current information, check the Aldebaran / Maxtronics manufacturer page or visit the official product page. Use the comparison tool to evaluate these trade-offs against competing robots in the same category.
How Research Robot Technology Works
Understanding the engineering behind this category
Research robots serve a fundamentally different purpose than commercial or consumer models. They are platforms for discovery — enabling scientists and engineers to test theories, develop algorithms, and push the boundaries of what robots can do. The technology in research robots prioritizes openness, flexibility, and access to raw data over consumer-friendly packaging or commercial reliability. Understanding this distinction is important for anyone considering a research robot platform.
Navigation & Mobility
Research robots typically expose their navigation systems at a much lower level than commercial products. Researchers can access raw sensor data, modify SLAM algorithms, implement custom path planners, and test novel navigation approaches. ROS (Robot Operating System) and ROS 2 compatibility is standard, providing a common framework for sharing navigation modules across the research community. This openness enables rapid iteration — a researcher can swap between different SLAM implementations, test new obstacle avoidance strategies, or develop entirely novel navigation paradigms without being locked into a vendor's proprietary stack.
The Role of AI
Research robots serve as physical testbeds for AI algorithms that may eventually appear in commercial products years later. Reinforcement learning, imitation learning, few-shot task learning, and human-robot interaction studies all require robot platforms that can execute AI-generated commands in the physical world. The gap between simulation (where training is cheap and fast) and reality (where physics is unforgiving) makes physical robot platforms essential for validating AI approaches. Research robots must support rapid deployment of new AI models without extensive integration work.
Sensor Fusion & Perception
Research platforms prioritize sensor modularity and data access. Standard mounting interfaces allow researchers to attach custom sensors alongside built-in ones. Raw sensor data streams (not just processed results) are accessible for developing novel perception algorithms. Precise time-stamping and synchronization across sensor streams enable accurate multi-modal fusion research. Many research robots include more sensors than strictly necessary for any single application, providing researchers with rich datasets for developing and testing new algorithms.
Power & Battery Management
Research robots balance operational runtime with practical lab use. Sessions of one to four hours are typical, with quick charging between experiments. Some research setups use tethered power for long-running experiments where battery limitations would interrupt data collection. Power monitoring and logging capabilities help researchers understand the energy costs of different behaviors and algorithms — important for developing efficient approaches that will eventually run on battery-constrained commercial systems.
Safety by Design
Research environments present unique safety challenges because robots are constantly being programmed with untested behaviors. Hardware safety limits (joint speed caps, force limits, emergency stops) must be robust regardless of software commands. Safety-rated monitored stop and speed monitoring ensure the robot cannot exceed safe operating parameters even when running experimental code. Collaborative operation standards apply when researchers work alongside the robot during experiments. Many labs implement layered safety with physical barriers for high-speed testing and open-area operation restricted to validated, lower-risk behaviors.
What's Next for Research Robots
Research robot platforms are becoming more accessible and capable. Cloud robotics enables remote experiment execution and shared datasets. Digital twins and high-fidelity simulators reduce the need for physical hardware time while improving sim-to-real transfer. Standardized benchmarks and open datasets enable fair comparison of results across labs. The democratization of robotics research — through lower-cost platforms, open-source software, and cloud infrastructure — is expanding who can contribute to advancing the field.
The NAO6 by Aldebaran / Maxtronics incorporates many of these technology pillars. For a detailed look at the specific sensors and components used in the NAO6, see the sensor analysis and connectivity sections above, or browse the complete components glossary for explanations of every technology used across the robotics industry.
NAO6 in the Research Market
How this robot compares in the research landscape
Aldebaran / Maxtronics has not publicly disclosed pricing for the NAO6, which is typical for enterprise-focused robotics platforms that offer customized solutions and direct-sales relationships.
With 7 sensor types, the NAO6 has an extensive sensor suite. This comprehensive sensing capability places it among the more perception-capable robots in the research category, enabling more robust autonomous operation in varied conditions.
Being currently available for purchase gives the NAO6 a practical advantage over competitors still in development or prototype stages. Buyers can evaluate the actual product rather than relying on spec-sheet promises that may change before release.
Head-to-Head Comparisons
Side-by-side specs, capability overlap analysis, and key differentiators.
For the full picture of Aldebaran / Maxtronics's portfolio and market strategy, visit the Aldebaran / Maxtronics manufacturer page.
Owning the NAO6: Setup, Maintenance & Tips
Practical guide from day one through years of ownership
Initial Setup
Research robot setup combines hardware assembly with software environment configuration. Unpack and assemble the platform following the manufacturer's documentation. Install the development framework — typically ROS or ROS 2 — and verify sensor connectivity. Calibrate all sensors using the manufacturer's tools and procedures. Set up the simulation environment (Gazebo, Isaac Sim, or equivalent) alongside the physical platform for parallel development. Establish version control for your experiment code and configuration. Document the initial calibration values and system state as your baseline for future reference. Plan network and computing infrastructure to handle the data rates your sensors will generate.
Ongoing Maintenance
Research robots need maintenance that preserves the precision required for valid experimental results. Regularly verify sensor calibration — drift in camera intrinsics or IMU biases can invalidate experiment data. Maintain clean workspace conditions to protect optical sensors. Document any hardware modifications or maintenance performed, as these can affect experimental reproducibility. Update software dependencies carefully, documenting versions used for each experiment. Joint and actuator wear in research robots that perform repetitive tasks should be monitored and factored into experimental design.
Software Updates & Long-Term Support
Research robot software updates require careful management to maintain experiment reproducibility. Document the exact software versions used for each experiment. Test updates in a separate environment before applying to your experiment platform. Contribute bug fixes and improvements back to the community when using open-source frameworks. Be aware that ROS and other framework updates may require code changes in your custom packages — budget time for integration testing after major framework updates.
Maximizing Longevity
Research robots often have longer productive lives than commercial products because they can be upgraded and repurposed. Extend your investment by maintaining clean mechanical and electrical systems, documenting all modifications for future lab members, and keeping spare parts for common wear items. When specific components become obsolete, community forums and lab networks can be valuable sources for replacements. Consider the platform's modularity when planning future research directions — a platform that can accept new sensors and actuators adapts to evolving research questions.
For Aldebaran / Maxtronics-specific support resources and documentation, visit the Aldebaran / Maxtronics page on ui44 or check the manufacturer's official website at Aldebaran / Maxtronics's product page.
Frequently Asked Questions
What is the NAO6?
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Data Integrity
All NAO6 data on ui44 is verified against official Aldebaran / Maxtronics sources, including spec sheets, product pages, and press releases. Last verified: 2026-03-26. Official source: Aldebaran / Maxtronics product page. If you find outdated or incorrect information, please let us know — accuracy is our top priority.
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