Humanoid Robotics Ecosystem & Omnidimensional Data

Renault Group is building its position in humanoid robotics and Physical AI. Making sense of a fast-moving, fragmented ecosystem — and of the many different kinds of data that robotics and Physical AI systems produce — is a precondition for any serious roadmap or partnership decision.

Two challenges at once: mapping the industrial and technology actors in the humanoid robotics space — start-ups, laboratories, suppliers — and how proof-of-concepts, partnerships and co-development tracks with them are progressing; and structuring what "robotics and Physical AI data" actually means across a physical system's lifecycle — sensor/kinematic/force data, human-robot interaction, simulation and digital twins, and the surrounding industrial-process, safety and ergonomics context — so it can be traced, quality-checked and reused.

Robotics & Physical AI Project Manager, coordinating robotics partners and internal teams across technology benchmarking, industrial mock-ups, use-case development, ecosystem mapping and data-foundation structuring as part of the broader Robotics & Physical AI roadmap.

The work combines partner and technology assessment with industrial use-case development. I coordinate teams benchmarking different robot brands and technologies across conventional industrial robots, collaborative robots, mobile robotics (including AMRs and mobile manipulators), humanoids and other emerging platforms. In parallel, I coordinate interactions with robotics partners — including the public Renault Group × Wandercraft collaboration — around industrial mock-ups and use-case realization, while maintaining ecosystem mapping and structuring reusable robotics/Physical AI data foundations for future AI training and robot behavior validation.

A data-foundation and ecosystem-structuring effort rather than a single technical system: its output is a reference model for robotics/Physical AI data (types, sources, quality, traceability, reuse) and an actor/initiative map, both still being built.

• Humanoid robotics ecosystem mapping
• Robot technology benchmarking
• Conventional / collaborative / mobile robotics
• Sensor / kinematic / force data
• Human-robot interaction data
• Simulation & digital twins
• AI data
• Data traceability & data quality
• Omnidimensional robotics data

1. Concept
2. Prototype
4. Validation
5. Industrialization
6. Deployment
7. Scale

• Led
• Designed
• Coordinated

Not yet industrialized/deployed — see Project journey above for the stage actually reached.

In progress: the objective is a structured, reusable robotics/Physical AI data foundation and an actionable map of the humanoid robotics ecosystem.

• Technology roadmapping
• Robot technology benchmarking
• Partner coordination
• Industrial use-case development
• Data architecture thinking
• Ecosystem / partnership mapping
• Cross-functional coordination
• Physical AI