Illustrative walkthrough · not a product screenshot or deployment
Explore the reasoning
Choose the task, embodiment and acceptance question for one experiment.
The decision behind the system
What must be proven before a robot experiment can act?
A robotics research programme joining provenance, dry runs, simulation and guarded deployment work. Related model and runtime experiments are presented as one research family.
This research family concerns learning and runtime experiments. Auralink addresses shared-resource coordination; the portfolio does not establish that all research components are integrated.
Evaluation before actuation
Reachy and SO-101 research paths use dry-run and simulation boundaries, with provenance and deployment controls kept explicit.
Phytral
A dual-system vision-language-action research prototype explores perception and action. Large-scale training and real-robot validation remain future work.
Runtime and distributed research
The Physical AI Stack explores local model/runtime catalogues and rollback. Embodied Intelligence Mesh explores distributed training, validation and inference in simulation.
Read the complete illustrative walkthrough
Define
Choose the task, embodiment and acceptance question for one experiment.
Trace
Record data and model provenance, configuration and the runtime boundary.
Exercise
Inspect a dry run or simulation, including failures and assumptions about the physical environment.
Qualify
Identify the separate evidence needed before hardware commissioning or transfer to another embodiment.
One inspectable artefact
Hyperion Robotics dry-run, simulation, provenance and guarded-deployment paths (source through 22 October 2026).
A current boundary
No physical commissioning or learned-policy success on real robots is established.
How to start
Scope a reproducible robotics experiment. Physical commissioning and learned-policy success on real robots are not established by these records.
These are source and research records. Illustrative examples do not establish deployment, integration, certification or customer outcomes.
Explorer le dossier technique et les preuves
Pont métier ↔ technologie · Connect robot learning research to a controlled evaluation path.
What must be proven before a robot experiment can act?
This research family concerns learning and runtime experiments. Auralink addresses shared-resource coordination; the portfolio does not establish that all research components are integrated.
Il s'agit d'une interprétation du portefeuille et des sources, et non d'une affirmation de client, déploiement, certification ou résultat.
01
Pression métier
A promising model experiment needs a reproducible path through data provenance, dry runs and simulation before physical actuation is considered.
02
Décision produit
Choose the task, embodiment and acceptance question for one experiment. Identify the separate evidence needed before hardware commissioning or transfer to another embodiment.
03
Dossier technique
Reachy and SO-101 research paths use dry-run and simulation boundaries, with provenance and deployment controls kept explicit. A dual-system vision-language-action research prototype explores perception and action. Large-scale training and real-robot validation remain future work. The Physical AI Stack explores local model/runtime catalogues and rollback. Embodied Intelligence Mesh explores distributed training, validation and inference in simulation.
04
Retour des preuves
Identify the separate evidence needed before hardware commissioning or transfer to another embodiment.
Preuves issues du code source
Ce que le code source permet réellement d’établir
A robotics research family joining the Hyperion Robotics integration record with related Phytral, Physical AI Stack and Embodied Intelligence Mesh experiments. Each component retains its own source and validation boundary.
Le relevé technique détaillé est maintenu en anglais.
Maturité
Robotics research · dry runs and simulation
Revue des preuves
État du code au
Décisions produit et architecture
Keep experiment provenance separate from claims of physical robot success.
Use dry-run and simulation evidence before seeking physical integration authority.
Treat model, runtime and distributed-system experiments as components of one research programme.
Éléments vérifiables
Hyperion Robotics dry-run, simulation, provenance and guarded-deployment paths (source through 22 October 2026).
Phytral dual-system vision-language-action prototype (1 June 2026) and Physical AI Stack host/runtime/model catalogue work (1 September 2026).
Embodied Intelligence Mesh simulated training, validation and inference vertical slice (25 June 2026).
Limites des affirmations
No physical commissioning or learned-policy success on real robots is established.
Large-scale model training and production GPU, ROS2, industrial and hardware adapters require separate validation.
Component source does not establish interoperability, safety certification or a completed integrated product.
Les preuves du dépôt ne constituent pas des preuves client, de déploiement, de certification ou de résultats.
Work with Hyperion
Frame a robotics experiment.
An experiment brief with provenance requirements, simulation criteria and a separate physical-validation gate.
Bring a short description of your situation, constraints and decision. We agree the scope, responsibilities and quote before work begins.