Cyberwave Research
Where embodied AI meets production reality
Cyberwave Research builds the science that turns frontier physical AI — robot foundation models, VLA policies, multi-robot orchestration, shared autonomy — into systems you can actually run on a factory floor, a logistics yard, an inspection route, a hospital, a power plant, or a forward defense site.
Our research thesis
Embodied intelligence is having its GPT moment. Foundation models can reason about physical tasks; VLA policies can act on them. The bottleneck has moved.
The frontier isn't just bigger models. It's the scaffolding around them — twins, fleets, safety envelopes, teleop pipelines, deterministic runtimes — that decides whether a clever policy becomes a clever demo or a system that runs 24/7 across factories, depots, ports, hospitals, and defense sites.
Cyberwave Research lives at that interface. We work on the models and we work on the production stack underneath them — because in physical AI you can't separate the two.
Research focus areas
Nine workstreams, one stack. Each one ships into the platform.
Robot Foundation Models (RFM)
We train and fine-tune large embodied policies that generalize across morphologies — arms, mobile bases, drones, humanoids — and across tasks. Our recipe blends imitation from teleoperation, RL in simulation, and continual learning from production telemetry, with safety constraints baked into the loss.
Vision-Language-Action (VLA) Policies
VLA models that turn natural-language goals like “inspect aisle seven” or “pick the damaged crate on pallet B” into grounded, low-latency action streams. We focus on the hard parts: spatial grounding, long-horizon planning, recovery behaviors, and predictable performance under degraded sensing.
Multi-Robot Orchestration
Heterogeneous fleets working together — UGVs, manipulators, drones, humans — across labs, factories, ports, and outdoor sites. We research scheduling, conflict resolution, shared perception, and resilience patterns that hold up when one node degrades or drops out.
Human-Robot Interaction
Operators rarely want full autonomy or full teleop — they want a dial. We build shared-autonomy interfaces, intent prediction, conversational supervision, and gesture-based hand-offs so a single person can safely supervise dozens of robots without losing situational awareness.
Sim-to-Real & Digital Twins
High-fidelity twins, domain randomization, photoreal sensor models, and hardware-in-the-loop rigs let us promote policies from simulation to production with measurable, statistical confidence — not vibes. Every regression suite runs in sim before any real motor moves.
Edge Autonomy & Deterministic Compute
Foundation-scale intelligence is useless if the control loop misses its deadline. We research model distillation, adaptive scheduling, mixed-precision inference, and deterministic runtimes so VLA-class policies can run at millisecond cadence on heterogeneous edge hardware.
Perception & Sensor Fusion
Vision, LiDAR, depth, thermal, acoustic, IMU, industrial telemetry — fused into a single, queryable world model. Robust under occlusion, weather, glare, vibration, and the messy reality of factory floors and outdoor sites.
Safety, Assurance & Governance
Runtime safety envelopes, formal monitors, override paths in milliseconds, and audit trails by default. We build the verification tooling that lets embodied AI ship into regulated environments — manufacturing, energy, healthcare, defense — and stay there.
Continual Learning from Fleets
Every deployment generates teleop traces, intervention events, and edge-case telemetry. We research how to safely curate, label, and re-train from this data — turning every robot in production into a contributor to the next model.
What ships out of the lab
Research at Cyberwave is judged by what reaches production — not what reaches a paper.
- Production-grade VLA policies for inspection, pick-and-place, and navigation, served from the edge with deterministic latency budgets.
- Open digital twin recipes and sim-to-real regression tooling shared with the ecosystem so others can promote policies safely.
- Safety cases and runtime monitors aligned with IEC 61508 and ISO 10218 so embodied AI can enter regulated environments and stay there.
- Shared-autonomy and teleop loops battle-tested across defense, logistics, energy, manufacturing, aerospace, and maritime deployments.
- Academic collaborations on embodied LLMs, tactile sensing, multi-agent coordination, and continual learning from real fleets.