FORGE H1 Egocentric Capture Hardware Case Study

DISCIPLINE

Industrial design

SCOPE

Product development

STAGE

Production support

CASE

FORGE H1

Industrial design · Product development

A focused case study in form, materials, and production support.

Why egocentric data is effective.

FORGE H1 captures how people see and act, turning everyday work into the data that helps robots learn useful skills for homes, workplaces, and beyond.

Scale / Real-world data

Hours of egocentric data in the paper’s comparison.

EgoMimic

55 h

EgoDex

829 h

Xperience-10M

1,059 h

EgoLive

1,680 h

Selected datasets from Table 1 · bars normalized to EgoLive

Signal density

1,680 h

65,866 episodes
346 tasks

Stereo RGB · Depth · 3D hands
Masks · Language

Spatial accuracy

3.1 mm

Mean depth error · 0.5 m

Within 10 mm

At 0.5 m

99.2%

At 0.9 m

87.1%

Source / Li et al. · EgoLive · Table 1 + Section 4.2 · arXiv 2604.23570
Source / Zheng et al. · EgoScale · Figure 5 · arXiv 2602.16710

EgoLive data capture examples with hand tracking overlays

Power reserve

1 pack

4 h

2 packs

8 h

Covering working hours around the clock.

One replaceable pack doubles the capture window.

Recording capacity

Internal

64 GB

microSD

128 GB

Seamless data exchange and collection.

At 120 Mbps≈18.5 hEstimated capture time with 1 TB

FORGE H1

Why egocentric data is effective.

1,680 h

3.1 mm

Power reserve

Recording capacity

What FORGE H1 can capture