QuantumLearning Machines
Engineering Workcell Shell / Robotics and precision handling

Robotics Lab V10

Robotics Lab becomes an engineering performance environment where learners make predictions, act, revise, transfer, and produce evidence.

Domain world

An engineering bay with constraints, telemetry, safety margins, iteration history, and failure recovery.

An engineering bay with constraints, telemetry, safety margins, iteration history, and failure recovery. This V10 profile is intentionally separate from the current Robotics Lab runtime until the new shell is built and validated.

six-axis robot armpath splinefragile payloadgripper force halocollision enveloperobot armfragile cargo
Learner contract
1goal
2prediction
3action
4observation
5explanation
6revision
7transfer
8evidence
First action

Tune grip force or sensor trust, predict the failure mode, then run the workcell.

V10 forbids blank-canvas confusion: the first action must be visible, meaningful, and produce a consequence.

Misconception traps
  • Too much grip crushes fragile objects
  • Too little grip drops cargo
  • Sensor confidence is not the same as ground truth
Adaptive intelligence
  • Add a new constraint
  • Force tradeoff between performance, safety, and cost
  • Increase transfer distance after strong explanation
  • Add scaffold when revision quality drops
  • Route repeated misconception to a repair micro-mission
Evidence engine
Processpredictionaction traceobservationexplanationrevision
CognitiveD1 conceptual modelD2 quantitative reasoningD3 uncertainty calibrationD4 communicationD5 transfer
CompetencyUC1 problem framingUC2 evidence useUC3 adaptive executionUC4 collaboration readinessUC5 ethical judgment
TeacherOSroboticslab misconception patternengineering intervention prioritynext best micro-intervention
QLM Proofclaimprocess evidencedefense prompttransfer artifactverification summary
Studio generation contract

What Studio must generate

  • mission contract
  • domain-authentic shell
  • variables and controls
  • misconception traps
  • TeacherOS evidence summary
  • QLM Proof-ready artifact
Readiness gates
One clear goal

The learner sees one mission goal before any controls compete for attention.

Visible first action

The first action is obvious, clickable/touchable, and visibly changes state.

Three meaningful decisions

The mission requires at least three choices where different reasoning produces different outcomes.

Misconception trap

The sim includes a likely misconception and captures evidence when the learner falls into or avoids it.

Revision opportunity

The learner can revise after observing consequences instead of being graded only on first output.

Transfer prompt

The learner applies the same reasoning to a new context before completion.

Teacher-readable evidence

TeacherOS can summarize prediction, action, observation, explanation, revision, and transfer.

Teacher value contract

The sim must resist cheating, reduce burnout, reduce grading time, maximize screen-time value, and support misconception-cluster feedback.

Teacher source control

Teacher-provided sources, datasets, documents, and research constraints must be preserved in the mission contract.

TeachProof recommendation

TeacherOS/TeachProof must recommend how the classroom simulation should have been run based on observed student events.

Grade-appropriate shell

The selected shell changes language density, controls, read-aloud, and scaffolding by grade band.

Accessibility baseline

The experience is Chromebook-safe, keyboard reachable, reduced-motion aware, and readable.

Visual distinctiveness

The sim is not a reskin: objects, controls, mission art, and success state are domain-specific.

Playable V10 missions

Pick one mission. Follow the guide. Submit evidence.

These are the original STEM missions upgraded into the V10 workflow: start, goal, controls, evidence, submit.

3-5 / 6-8 / 9-12 / undergrad · roboticslab shell

Reach the Target

Save a prediction about whether grip, path, or speed will cause the failure

targetRun Robot Arm
Launch guided mission