
Mixed Object Picking
Evaluate perception, grasp planning and autonomous recovery across changing objects and physical conditions.
Scenario detailSimulation and lab benchmarks describe capability. Reality describes readiness. RealForge gives robotics and Physical AI teams structured access to environments they could not otherwise reach.
Describe the physical conditions your system needs to meet and the behaviour you need to observe.
We identify facilities in the network whose real operating conditions correspond to that scenario.
Your system runs under authentic conditions while observation is captured in a consistent structure.
Results are read across sites, regions and conditions rather than against a single controlled baseline.
A system is only as good as the conditions it has survived.
Controlled environments reward consistency. Real facilities reward recovery — from variance, from interruption, from the ordinary disorder of a working shift.
Structured observations from every run, described the same way across every site, so performance patterns can be read at scenario level and across environments.
We do not publish comparative rankings of the systems in the network, and we do not manufacture figures to fill a chart.