SE01 vs NAO V6: Specs, Price & ROS Support Compared (2024)
EngineAI Robotics vs Aldebaran (Maxvision) — independent, side-by-side analysis.
Quick Verdict
SE01 leads in more DOF, longer runtime, faster speed, while NAO V6 leads in lower price. Overall, SE01 has an edge in 3 out of 4 compared categories.
SE01
EngineAI Robotics
NAO V6
Aldebaran (Maxvision)
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SE01 NAO V6
Specifications
$20,000Price$16,990
170 cmHeight58 cm
55 kgWeight5.6 kg
32DOF25
—Payload—
2hRuntime1h
2 m/sSpeed0.5 m/s
YesStairsNo
YesLiDARNo
N/AComputeIntel Atom (upgraded in V6)
Ecosystem Openness
—
SE01
/100
70
NAO V6
NAOqi + Choregraphe. Massive academic community. Future uncertain post-bankruptcy.
Pros and cons at a glance
SE01
Pros
- Shipping to customers (verified commercial availability)
- Ships with LiDAR for robust depth sensing in low-light environments
- 32 degrees of freedom — full-body articulation
Cons
- Short runtime (120 min) — frequent recharging or battery swaps
- Closed software stack — no public SDK or ROS support
NAO V6
Pros
- Shipping to customers (verified commercial availability)
- Affordable at $16,990 — accessible to research labs and SMEs
Cons
- Short runtime (75 min) — frequent recharging or battery swaps
- Cannot navigate stairs — restricts deployment environments
Frequently asked questions
Which is cheaper: SE01 or NAO V6?
NAO V6 is cheaper at $16,990 vs $20,000 for SE01. Note that lower price does not imply lower total cost of ownership — see the TCO calculator on the Explore page for utilisation-adjusted figures.
Are both SE01 and NAO V6 shipping to customers?
Yes. Both are commercially available as of the last review. Delivery timelines and customer geographies vary per vendor — check the manufacturer page for each.
Which is better for ROS-based development: SE01 or NAO V6?
SE01 has no ROS support; NAO V6 has ROS 1 only. For research and multi-vendor robotics stacks, native ROS 2 is the strongest signal of ecosystem maturity.
Does SE01 or NAO V6 use LiDAR?
SE01 ships with LiDAR for depth sensing; NAO V6 does not. LiDAR adds cost and complexity but improves obstacle detection in low-light or low-contrast environments.
Last updated: 2024