Research Project
Mars Science Helicopter Processor
Research Team
Lead Researchers:
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Xiaojun (Ashely) Geng, Electrical and Computer Engineering
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Bingbing Li, Manufacturing Systems Engineering
Collaborators:
Student Team:
- Sara Ali, BS Computer Engineering
- Aditi Kashyap, MS Electrical Engineering
- Matthew White, BS Electrical Engineering
- Yannis Nyemeck-ndjip, BS Electrical Engineering
- Jared Carrillo, BS Mechanical Engineering
Funding
- Funding Organization:
- Funding Program:
SYNOPSIS
- Developing a Mars-ready airframe for the Mars Science Helicopter
- Designing a robust data transfer system for the primary and spare processors for the state estimator of a Mars Science Helicopter
- Creating an emergency landing system for the Mars Science Helicopter in case of system failure
Research Questions and Research Objectives
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Determining essential data packages required for the spare processor to ensure seamless mission continuity
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Designing a bi-directional data exchange pathway between the primary and spare systems to ensure reliable data transfer and minimize latency for mission-critical and time-sensitive functions
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Developing a mechanism to activate the emergency landing system in the event of a malfunction in both the primary and spare systems
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Prototyping the entire navigation system, and validating the design
Research Methods
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Identify the requirements and constraints for each project objective
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Divide each project objective into small tasks and develop a timeline
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Perform literature review on fault-tolerant data transfer methods, and state estimation algorithms
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Evaluate various potential design solutions in terms of reliability, efficiency, and complexity, to select the most suitable approach
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Document the entire research process, including design decisions, testing results, and any modifications
Research Results and Deliverables
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A robust navigation system for the Mars Science Helicopter that is resilient to processor fault recovery
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An emergency landing system for the Mars Science Helicopter, preventing the helicopter from crashing
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A prototyping system that demonstrates resilience to injected processor faults
Commercialization and/or Societal Impact Opportunities
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Applicable to any crucial task requiring a fail-safe mechanism
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Adaptable to commercial drones for search and rescue, surveying, and delivery
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Useful to improve the safety and reliability of self-driving cars by ensuring real-time sensor fusion and redundant data storage
Research Timeline
Start Date:
End Date:
Lead Researchers:
-
Xiaojun (Ashely) Geng, Electrical and Computer Engineering
-
Bingbing Li, Manufacturing Systems Engineering
Collaborators:
Student Team:
- Sara Ali, BS Computer Engineering
- Aditi Kashyap, MS Electrical Engineering
- Matthew White, BS Electrical Engineering
- Yannis Nyemeck-ndjip, BS Electrical Engineering
- Jared Carrillo, BS Mechanical Engineering
Funding
- Funding Organization:
- Funding Program: