GR-1 vs SE01: Specs, Price & ROS Support Compared (2024)
Fourier Intelligence vs EngineAI Robotics — independent, side-by-side analysis.
Schnellurteil
GR-1 leads in more DOF, while SE01 leads in longer runtime, faster speed. Overall, SE01 has an edge in 2 out of 3 compared categories.
GR-1
Fourier Intelligence
SE01
EngineAI Robotics
DNA-Overlay
GR-1 SE01
Spezifikationen
~$150,000–$170,000Preis$20,000
165 cmHöhe170 cm
55 kgGewicht55 kg
40FHG32
50 kgNutzlast—
1hLaufzeit2h
1.39 m/sGeschwindigkeit2 m/s
JaTreppenJa
NeinLiDARJa
NVIDIA Isaac Lab ecosystemRecheneinheitN/A
Ökosystem-Offenheit
65
GR-1
/100
—
SE01
ROS + Isaac Lab + MuJoCo. Growing research community.
Pros and cons at a glance
GR-1
Pros
- Shipping to customers (verified commercial availability)
- High rated payload (50 kg) for industrial pick-and-place
- 40 degrees of freedom — full-body articulation
Cons
- Unit price not publicly disclosed (quote-on-request or enterprise-only)
- Short runtime (60 min) — frequent recharging or battery swaps
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
Frequently asked questions
How do GR-1 and SE01 compare on price?
GR-1: ~$150,000–$170,000. SE01: $20,000. Only one of the two has a public unit price; the other publishes a range or enterprise-only terms.
Are both GR-1 and SE01 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: GR-1 or SE01?
GR-1 has ROS 1 only; SE01 has no ROS support. For research and multi-vendor robotics stacks, native ROS 2 is the strongest signal of ecosystem maturity.
Does GR-1 or SE01 use LiDAR?
SE01 ships with LiDAR for depth sensing; GR-1 does not. LiDAR adds cost and complexity but improves obstacle detection in low-light or low-contrast environments.
Zuletzt aktualisiert: 2024