PhD Proposal by Kerianne Hobbs

Event Details
  • Date/Time:
    • Tuesday December 11, 2018
      12:00 pm - 2:00 pm
  • Location: Montgomery Knight Room 325
  • Phone:
  • URL:
  • Email:
  • Fee(s):
  • Extras:
No contact information submitted.

Summary Sentence: Verified Automatic Collision Avoidance for Spacecraft

Full Summary: No summary paragraph submitted.

Kerianne Hobbs
(Advisor: Prof. Feron)

will propose a doctoral thesis entitled,

Verified Automatic Collision Avoidance for Spacecraft


Tuesday, December 11 at 12:00 p.m.
Montgomery Knight Room 325


How can safety be assured for spacecraft automatic collision avoidance? Answering this question is a Verification and Validation research endeavor. Verification confirms that a system element design meets specifications, while validation confirms that a set of requirements appropriately and adequately describes the capability or functionality of the system element. In order to verify and validate collision prediction and avoidance maneuvers, a set of specifications or requirements will be developed for the research.


The proposed work will focus on verifying safety of automatic avoidance maneuvers for spacecraft, with considerations for uncertain initial conditions and perturbations. Following the aircraft literature, there are two general approaches to collision avoidance: 1) maneuver far in advance when uncertainty is high and fuel can be conserved, but may be expended unnecessarily 2) maneuver near the last instant when uncertainty is low and the need to maneuver is certain, but an aggressive maneuver may expend excess fuel.


The primary contribution of the proposed work is anticipated to be development and formal verification of pre-scripted template-based automatic maneuver approaches for last instant collision avoidance. This approach may better facilitate collision avoidance maneuver computation on board spacecraft embedded processors as well as formal verification of the maneuvers within an integrated system. While work has been completed for automatic avoidance maneuvers using model predictive control, stochastic optimal control, and robust optimal control, these approaches are not computationally tractable to do on board. Future missions and operations in increasingly congested environments will require more agile and assured methods that considered stochastic uncertainty.



  • Prof. Eric Feron – School of Aerospace Engineering (advisor), Georgia Institute of Technology
  • Prof. Glenn Lightsey – School of Aerospace Engineering, Georgia Institute of Technology
  • Prof. Moriba Jah – School of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin

Additional Information

In Campus Calendar

Graduate Studies

Invited Audience
Faculty/Staff, Public, Graduate students, Undergraduate students
Phd proposal
  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: Nov 26, 2018 - 1:51pm
  • Last Updated: Nov 26, 2018 - 1:51pm