About

Dr. Ella Atkins is the Fred D. Durham Professor and Head of the Kevin T. Crofton Department of Aerospace and Ocean Engineering at Virginia Tech. She holds a Ph.D. in Computer Science & Engineering from the University of Michigan, as well as M.S. and B.S. degrees in Aeronautics and Astronautics from MIT. Her research focuses on AI-enabled autonomy and control to support resilience and contingency management in manned and unmanned aerospace applications, with particular emphasis on Advanced Air Mobility and Uncrewed Aircraft Systems (UAS). Dr. Atkins has authored over 250 refereed journal and conference papers and is the Editor-in-Chief of the AIAA Journal of Aerospace Information Systems (JAIS). She is also a Fellow of the American Institute of Aeronautics & Astronautics (AIAA). Her professional service includes roles such as Editor-in-Chief, executive steering committee memberships, and participation in various national and international aerospace and robotics initiatives. She has previously served as a Professor at the University of Michigan, where she was involved in aerospace engineering and robotics departments, and has held positions in industry and academia dedicated to advancing aerospace autonomy and information systems.

Research topics

• Computer Science
• Artificial Intelligence
• Machine Learning
• Statistics
• Mathematics
• Distributed computing
• Simulation
• Transport engineering
• Engineering
• Automotive engineering

Selected publications

• Feasibility Assurance for Search-Based Emergency Landings

  2026-01-08

  articleSenior author

  This paper presents an approach to ensure kinematic and dynamic feasibility in discrete search-based aircraft emergency landing planning by determining a set of fundamental aircraft maneuvers that remain well bounded within the degraded operational envelope under steady wind conditions. These maneuvers form the action set for an airspace-aware contingency landing planner. Kinematic analysis and parametric optimization across varying wind conditions and course changes are performed for an engine-out Cessna 182 to generate dynamically feasible landing trajectories. A Washington, D.C. case study demonstrates that the dynamically simulated aircraft closely follows the discrete search-generated emergency landing trajectory with minimal tracking error and bounded airspeed. The robustness of the proposed approach is further evaluated through a series of emergency landing dynamic simulations under different wind conditions, confirming its capability to maintain feasibility and safety even under strong wind. Future work will incorporate stochastic wind and turbulence models into the planner.

  PublisherDOI

• Iterative Repair for Small Satellite Power, Attitude and Mission Task Schedule Management

  2026-03-07

  articleSenior author

  Onboard plan repair is critical to next generation small spacecraft, especially those increasingly tasked with high bandwidth data processing tasks that place high demands on stored energy and guidance, navigation, and control (GNC) support. This paper investigates the application of a lightweight iterative repair task scheduling algorithm to a Low Earth Orbit (LEO) space science satellite mission. Iterative repair begins with a working schedule and updates this schedule in real-time based on new information or emerging constraint conflicts. In common scenarios, task execution delays accumulate due to small deviations in allocated execution times, requiring modest timeline updates. More significant delays or task execution failures can result in iterative repair seeking assistance, coordinating with mission operators to define a new schedule beyond the scope of what iterative repair can manage. This paper contributes a space-science based rescheduling implementation grounded in GNC slewing physics, orbital dynamics, and solar energy recharge equations to realistically optimize onboard satellite task management. Three test cases of increasing complexity are analyzed, showing iterative repair can react quickly and appropriately manage required schedule updates. Future work will extend models to include communications and realistic data processing task models, multiprocessor scheduling, and meta-scheduling to consider tradeoffs in building new schedules and rescheduling onboard.

  PublisherDOI

• Airspeed Forward-Invariance for Unpowered Fixed-Wing Aircraft

  ArXiv.org · 2026-04-22

  articleOpen accessSenior author

  Autonomous fixed-wing flight is becoming a key capability in aerial robotics, enabling sensing, mobility, and contingency operations across both small-scale Uncrewed Aircraft Systems and large-scale Advanced Air Mobility. During unpowered operation in fixed-wing platforms, airspeed is regulated solely through potential-kinetic energy exchange, making airspeed dynamics highly sensitive to guidance commands, particularly under wind. This paper presents a viability-based airspeed protection for ground-referenced guidance in steady wind, where airspeed evolution depends explicitly on the commanded flight path angle. Leveraging Nagumo's tangency condition, we derive a closed-form, wind-dependent characterization of admissible guidance commands that guarantees forward invariance of a safe airspeed envelope. These conditions are embedded within an offline quadratic programming framework to certify airspeed-safe maneuver primitives for non-ascending flight at the guidance level. The approach is validated using a high-fidelity unpowered fixed-wing aircraft model on gliding trajectories formed by concatenating certified maneuver primitives, demonstrating strict airspeed boundedness. Future work will address unsteady wind fields and flight experiments.

  PublisherOA PDF

• Airspeed Forward-Invariance for Unpowered Fixed-Wing Aircraft

  arXiv (Cornell University) · 2026-04-22

  preprintOpen accessSenior author

  Autonomous fixed-wing flight is becoming a key capability in aerial robotics, enabling sensing, mobility, and contingency operations across both small-scale Uncrewed Aircraft Systems and large-scale Advanced Air Mobility. During unpowered operation in fixed-wing platforms, airspeed is regulated solely through potential-kinetic energy exchange, making airspeed dynamics highly sensitive to guidance commands, particularly under wind. This paper presents a viability-based airspeed protection for ground-referenced guidance in steady wind, where airspeed evolution depends explicitly on the commanded flight path angle. Leveraging Nagumo's tangency condition, we derive a closed-form, wind-dependent characterization of admissible guidance commands that guarantees forward invariance of a safe airspeed envelope. These conditions are embedded within an offline quadratic programming framework to certify airspeed-safe maneuver primitives for non-ascending flight at the guidance level. The approach is validated using a high-fidelity unpowered fixed-wing aircraft model on gliding trajectories formed by concatenating certified maneuver primitives, demonstrating strict airspeed boundedness. Future work will address unsteady wind fields and flight experiments.

  PublisherDOI

• Multi-Aircraft Energy-Optimal Route Planning for Advanced Air Mobility

  2026-01-08

  articleSenior author

  Advanced Air Mobility (AAM) will require scalable methods for routing large numbers of increasingly autonomous aircraft through dense four-dimensional (4D) urban airspace volumes. This paper presents a decentralized multi-aircraft path-planning framework that formulates motion planning as a discrete-time graph search problem built from feasible kinematic maneuver primitives. Each vehicle performs an A* search over a dynamically constructed hybrid discrete-continuous state space, while a two-tier geofencing architecture and 4D occupancy tensor provide lightweight, decoupled conflict avoidance. Monte Carlo simulations evaluate performance across a range of traffic densities, demonstrating computational efficiency, energy-aware routing, and strong scalability. Case study results indicate a sub-second planning time per vehicle and illustrate how geofence extent impacts maximum airspace occupancy. Due to defined cost and heuristic function weights, the planning algorithm has a consistent preference for delaying departure time rather than generating circuitous paths with altitude changes when resolving spatiotemporal conflicts. This approach contributes a practical, ConOps-aligned solution to large-scale AAM multi-agent path finding and provides a foundation for future integration with service-provider traffic management architectures.

  PublisherDOI

• The Anatomy of Autonomy

  2026-03-11

  article

  Join us for a discussion of the book *The Anatomy of Autonomy*.

  PublisherDOI

• Airspace-aware Contingency Landing Planning

  arXiv (Cornell University) · 2026-02-06

  articleOpen accessSenior author

  This paper develops a real-time, search-based aircraft contingency landing planner that minimizes traffic disruptions while accounting for ground risk. The airspace model captures dense air traffic departure and arrival flows, helicopter corridors, and prohibited zones and is demonstrated with a Washington, D.C., area case study. Historical Automatic Dependent Surveillance-Broadcast (ADS-B) data are processed to estimate air traffic density. A low-latency computational geometry algorithm generates proximity-based heatmaps around high-risk corridors and restricted regions. Airspace risk is quantified as the cumulative exposure time of a landing trajectory within congested regions, while ground risk is assessed from overflown population density to jointly guide trajectory selection. A landing site selection module further mitigates disruption to nominal air traffic operations. Benchmarking against minimum-risk Dubins solutions demonstrates that the proposed planner achieves lower joint risk and reduced airspace disruption while maintaining real-time performance. Under airspace-risk-only conditions, the planner generates trajectories within an average of 2.9 seconds on a laptop computer. Future work will incorporate dynamic air traffic updates to enable spatiotemporal contingency landing planning that minimizes the need for real-time traffic rerouting.

  PublisherOA PDF

• Energy-Optimal Traversal Between Hover Waypoints for Lift+Cruise Electric-Powered Aircraft

  Journal of Guidance Control and Dynamics · 2026-03-18 · 1 citations

  articleSenior author

  Advanced air mobility aircraft require energy-efficient flight plans to be economically viable. This paper defines minimum-energy direct trajectories between waypoints for [Formula: see text] electric vertical takeoff and landing (eVTOL) aircraft. Energy consumption is optimized over accelerated and cruise flight profiles with consideration of mode transitions. Because eVTOL operations start and end in hover for vertical takeoff and landing, hover waypoints are utilized. Energy consumption is modeled as a function of airspeed for each flight mode, providing the basis to prove energy optimality for multimode traversal. Wind magnitude and direction dictate the feasibility of straight-line traversal because [Formula: see text] aircraft point into the relative wind direction but also have a maximum heading-rate constraint due to finite yaw control authority. Energy and power use for an experimentally validated QuadPlane small eVTOL aircraft are characterized with respect to airspeed and acceleration in all flight modes. Optimal QuadPlane traversals are presented. Constraints on acceleration and wind are derived for straight-line QuadPlane traversal. Results show an optimal QuadPlane 500 m traversal between hover waypoints saves 71% energy compared to pure vertical flight traversal for a representative case study with a direct [Formula: see text] crosswind. Energy-optimal eVTOL direct trajectory definition with transitions to and from hover is novel to this work. Future work should model flight in three-dimensional wind and optimize maneuver primitives when required.

  PublisherDOI

• Airspace-aware Contingency Landing Planning

  Open MIND · 2026-02-06

  preprintSenior author

  This paper develops a real-time, search-based aircraft contingency landing planner that minimizes traffic disruptions while accounting for ground risk. The airspace model captures dense air traffic departure and arrival flows, helicopter corridors, and prohibited zones and is demonstrated with a Washington, D.C., area case study. Historical Automatic Dependent Surveillance-Broadcast (ADS-B) data are processed to estimate air traffic density. A low-latency computational geometry algorithm generates proximity-based heatmaps around high-risk corridors and restricted regions. Airspace risk is quantified as the cumulative exposure time of a landing trajectory within congested regions, while ground risk is assessed from overflown population density to jointly guide trajectory selection. A landing site selection module further mitigates disruption to nominal air traffic operations. Benchmarking against minimum-risk Dubins solutions demonstrates that the proposed planner achieves lower joint risk and reduced airspace disruption while maintaining real-time performance. Under airspace-risk-only conditions, the planner generates trajectories within an average of 2.9 seconds on a laptop computer. Future work will incorporate dynamic air traffic updates to enable spatiotemporal contingency landing planning that minimizes the need for real-time traffic rerouting.

  DOI

• Shifting Underactuated Configuration Variables in Aerial Manipulation by Adding an Actuated Arm

  2025-05-14

  article

  Multicopter uncrewed aircraft systems (UAS) commonly use parallel rotors to create body-fixed thrust and torque for control, leaving these systems underactuated. Under-actuation poses a significant challenge in tasks where attitude is critical, such as in collision-based aerial manipulation. Planning and control of system state at collision is required to ensure safe post-collision recovery. In particular, setting up pre-impact states such that impulses do not produce moments about mass centers can ensure recoverable departure velocities. To address the underactuated nature of UAS for collision-based aerial manipulation, this paper presents a UAS with an attached actuated pogostick. While the UAS with actuated pogostick is still underactuated, closing a control loop on the collision variables critical to managing collision response becomes possible with the new system equations. The proposed approach leverages an optimal trajectory planner coupled with a run-time controller based on partial feedback linearization of the UAS with actuated pogostick. Results show that the addition of the actuated pogostick enables setup for recoverable post-collision states when given dynamically feasible trajectories from the optimal trajectory planner.

  PublisherDOI

Recent grants

• CAREER: State-dependent Resource Management for Integrated Task and Motion Plans

  NSF · $160k · 2007–2009

• CPS: Small: Cyber-Physical Communication for Cooperative Human-Robot Mobility

  NSF · $500k · 2017–2021

Frequent coauthors

• Hossein Rastgoftar

  49 shared

• Ilya Kolmanovsky

  University of Michigan–Ann Arbor

  38 shared

• Wei Shyy

  University of Hong Kong

  26 shared

• Dawn M. Tilbury

  University of Michigan–Ann Arbor

  18 shared

• Yu Yao

  Nanjing University of Posts and Telecommunications

  17 shared

• Kang G. Shin

  Ann Arbor Center for Independent Living

  16 shared

• Jeremy Castagno

  University of Michigan–Ann Arbor

  16 shared

• John Broderick

  16 shared

Awards & honors

• AIAA Fellow (2019)
• AIAA Intelligent Systems Award (2022)
• University of Michigan Robotics Leadership Award (2020)
• NSF CAREER Award (2004-2009)
• Sloan Foundation Pre-Tenure Leave Fellowship (2002-2003)