Robotics

What is Robotics?

The hard constraint in robotics is that a mistake happens in the physical world. Robotics separates the two halves of the problem accordingly: planning and reasoning about a task, which benefits from a model, and enforcing the envelope the machine may operate within, which must not. The safety plane is deterministic — velocity, force, workspace and stop conditions are rules no model output can override. Planning proposes; the safety plane disposes.

Problems it solves

• Plan a robot task from a described goal
• Simulate before executing in the physical world
• Enforce velocity, force and workspace limits deterministically
• Analyse operational safety across a fleet
• Keep the reasoning behind a plan reviewable

Key capabilities

Deterministic Safety Plane

Physical limits are enforced by deterministic rules that no model output can override.

Simulation Setup

Turn a described physical problem into a solver configuration with its assumptions written down.

Deterministic Policy Engine

Rules, not inference, decide what is allowed to proceed — so a model can advise and never authorise.

Risk Scoring

Score a change, a lot or a habitat on a published rubric you can read component by component.

Evidence Trail

Every figure carries the record it came from, so a reader can check the answer instead of trusting it.

How it is built

Deterministic safety plane

Limits are rules, not inferences. No model output can widen the envelope.

Simulate first

Plans are examined in simulation before they reach hardware.

Fleet-level view

Operational safety analysed across machines rather than one at a time.

How it works

How the work is structured, and what each step's output rests on.

1. 1

   Describe the task

   Source

   State the goal and the environment.

2. 2

   Plan

   AI-inferred

   Produce a candidate task plan.

3. 3

   Simulate

   Observed

   Examine the plan in simulation.

4. 4

   Check the envelope

   Source

   The deterministic safety plane accepts or rejects the plan.

5. 5

   Execute under limits

   Source

   Run with the envelope enforced independently of the planner.

Example use cases

Each example has its own page you can read and share.

Ask Robotics

Illustrative examples. Results depend on your own data.

• “Plan a pick-and-place sequence for this cell.”
• “What does simulation say about this trajectory?”
• “Which planned motions were rejected by the safety plane, and why?”
• “Where is the fleet spending most of its stopped time?”

Security, governance and human control

Where the software deliberately limits itself.

Questions

Can the AI change safety limits?

No. The safety plane is deterministic and independent of the planner. That separation is the design.

Does it replace a safety assessment?

No. It enforces configured limits; regulatory and site safety assessment remains a human and organisational responsibility.