Guide-linked quiz · Medium Level

AI in Space and Satellites Quiz

Explore onboard autonomy for rovers and satellites, including science targeting, image processing, path planning, and communication limits.

Related guide pathsAI In Space And Satellites
Question 1 of 8

Why can Mars rover commands not be controlled like a real-time joystick?

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  1. Why can Mars rover commands not be controlled like a real-time joystick?
    • Radio signal travel takes minutes each way and the delay varies with Earth–Mars distance
    • Mars has no radio relay hardware
    • The rover has no onboard computer
    • The rover communicates only through visible light
  2. What does ESA’s Φsat-2 onboard cloud-detection application do with obscured Earth images?
    • It reconstructs all missing ground pixels with certainty
    • It filters images obscured by clouds so clearer images can be prioritized for downlink
    • It routes images to a Mars rover
    • It turns every image into a weather forecast
  3. What is the purpose of SpaceX Starlink’s autonomous collision-avoidance system discussed in the FCC order?
    • To classify galaxies from telescope images
    • To select SuperCam science targets on Mars
    • To maneuver satellites in response to conjunction risks with other space objects
    • To filter clouds from Earth-observation images
  4. How does NASA define the goal of avionics radiation-hardness assurance?
    • Guaranteeing software contains no bugs
    • Removing the need to test hardware in radiation environments
    • Increasing radio signal speed between Earth and Mars
    • Ensuring space-system electronics meet design specifications after radiation exposure
  5. What does NASA’s LSTM-based spacecraft software catalog entry identify as its purpose?
    • Detecting anomalies in spacecraft telemetry with machine-learning methods
    • Generating satellite images from text prompts
    • Choosing water-treatment chemical doses
    • Predicting wildlife species from camera-trap images
  6. Which astronomy task does NASA’s supervised-learning example apply to TESS observations?
    • Scheduling drinking-water pumps
    • Classifying transiting exoplanet candidates
    • Detecting gunshots in forest recordings
    • Predicting tax return accuracy
  7. What science target can NASA’s AEGIS system select autonomously for a rover instrument?
    • A future Starlink collision maneuver
    • A water-demand forecast for a city
    • A target for a remote-sensing instrument such as Perseverance’s SuperCam
    • A crop-weed label for an Earth farm
  8. What does Perseverance’s AutoNav system do when planning a drive?
    • Controls the rover continuously from Earth in real time
    • Selects tax records for anomaly audits
    • Filters every cloud from Earth-observation images
    • Builds a 3D terrain map, identifies hazards and plans a route around obstacles

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