Institutional precision

RobotSpace.ai Robotics Academy (R2A) · School-ready STEM, robotics and AI for ages 5–18

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Target platformautobotlabs.ai Sandbox Analytics
Evaluation modelReal-time structural analysis — static & runtime
Total evaluation100 marks per challenge

Functional Success

40 marks

Evaluates whether the digital twin successfully resolved the mission constraints.

Optimal40 marks

The robot completes 100% of the target objectives (e.g., cleared the maze, safely parked) without a single physical collision or boundary violation.

Functional25 marks

The robot achieves the primary end-state, but registers minor tracking errors, wall clipping, or momentary boundary slips.

Partial10 marks

The robot executes initial steps correctly but stalls, spins out, or fails midway through the spatial target.

Fail0 marks

The script triggers a fatal runtime error, or the robot fails to move completely.

Structural Efficiency

25 marks

Evaluates the cleanliness of the algorithm — the platform active-counts total block/line usage to penalize bloated code.

Excellent25 marks

The code utilizes the absolute minimum number of required structural lines, leveraging loops (Repeat, While) to compress repetitive tasks.

Satisfactory15 marks

The algorithm works perfectly but contains redundant blocks — e.g. stacking five "Move Forward" blocks instead of a single Repeat 5 loop.

Inefficient5 marks

Excessive nesting or redundant logic loops that waste virtual processing resources.

Sensor & Closed-Loop Integration

20 marks

Evaluates whether the student relies on hard-coded time steps or dynamic feedback loops.

Closed-Loop Mastery20 marks

The robot makes real-time navigation decisions based on continuous sensor polling — e.g. stopping exactly if ultrasonic distance < 10cm.

Open-Loop Dependency10 marks

The code uses raw time estimations (e.g. Move Forward for 3.4 seconds) instead of sensors — it will fail if obstacle locations change.

No Integration0 marks

Sensors are completely ignored or configured with broken logic gates — e.g. checking an inactive bumper sensor port.

Runtime Performance & Execution Time

15 marks

Evaluates execution speed and processor strain inside the autobotlabs.ai engine.

Optimal Paths15 marks

The robot calculates the fastest path with smooth angular transitions, drawing minimum virtual battery draw.

Erratic Movement10 marks

The robot exhibits jerky, constant over-corrections (common in poorly tuned single-sensor line-tracking logic), significantly increasing travel time.

System Strain5 marks

The script forces an unintentional infinite calculation loop without a mandatory wait command, creating performance drops on the host computer.

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For questions on how the automated rubric scores a specific challenge, or how it maps to classroom grading, reach out directly — our academy team responds within 2 business days.