About

Professor Jack Langelaan is a faculty member in Penn State's Department of Aerospace Engineering, which has a distinguished record of research excellence and scholarship. The department's research spans traditional disciplines associated with aeronautics and astronautics, with particular strengths in rotorcraft and aero-acoustics. The department is also expanding into new areas driven by increasing computational power for design, analysis, on-board autonomy, sustainable aviation, and space systems. The faculty include experienced researchers and emerging scholars, with notable accomplishments such as leadership in the Vertical Lift and Rotorcraft Center of Excellence, participation in large multidisciplinary research efforts including NASA initiatives, and recognition through numerous awards and society fellowships. Professor Langelaan's work contributes to these diverse research areas, supporting graduate research and fostering collaborations across the university and industry.

Research topics

• Computer Science
• Physics
• Simulation
• Mechanics
• Aerospace engineering
• Mathematics
• Engineering
• Classical mechanics
• Meteorology
• Environmental science
• Control engineering
• Mechanical engineering
• Statistics
• Acoustics

Selected publications

• Distributed State Estimation for Vision-Based Cooperative Slung Load Transportation in GPS-Denied Environments

  2026-01-08

  articleOpen access

  Transporting heavy or oversized slung loads using rotorcraft has traditionally relied on single-aircraft systems, which limits both payload capacity and control authority. Cooperative multilift using teams of rotorcraft offers a scalable and efficient alternative, especially for infrequent but challenging “long-tail” payloads without the need of building larger and larger rotorcraft. Most prior multilift research assumes GPS availability, uses centralized estimation architectures, or relies on controlled laboratory motion-capture setups. As a result, these methods lack robustness to sensor loss and are not viable in GPS-denied or operationally constrained environments. This paper addresses this limitation by presenting a distributed and decentralized payload state estimation framework for vision-based multilift operations. Using onboard monocular cameras, each UAV detects a fiducial marker on the payload and estimates its relative pose. These measurements are fused via a Distributed and Decentralized Extended Information Filter (DDEIF), enabling robust and scalable estimation that is resilient to individual sensor dropouts. This payload state estimate is then used for closed-loop trajectory tracking control. Monte Carlo simulation results in Gazebo show the effectiveness of the proposed approach, including the effect of communication loss during flight.

  PublisherOA PDFDOI

• Distributed State Estimation for Vision-Based Cooperative Slung Load Transportation in GPS-Denied Environments

  arXiv (Cornell University) · 2026-03-04

  preprintOpen access

  Transporting heavy or oversized slung loads using rotorcraft has traditionally relied on single-aircraft systems, which limits both payload capacity and control authority. Cooperative multilift using teams of rotorcraft offers a scalable and efficient alternative, especially for infrequent but challenging "long-tail" payloads without the need of building larger and larger rotorcraft. Most prior multilift research assumes GPS availability, uses centralized estimation architectures, or relies on controlled laboratory motion-capture setups. As a result, these methods lack robustness to sensor loss and are not viable in GPS-denied or operationally constrained environments. This paper addresses this limitation by presenting a distributed and decentralized payload state estimation framework for vision-based multilift operations. Using onboard monocular cameras, each UAV detects a fiducial marker on the payload and estimates its relative pose. These measurements are fused via a Distributed and Decentralized Extended Information Filter (DDEIF), enabling robust and scalable estimation that is resilient to individual sensor dropouts. This payload state estimate is then used for closed-loop trajectory tracking control. Monte Carlo simulation results in Gazebo show the effectiveness of the proposed approach, including the effect of communication loss during flight.

  PublisherDOI

• Generalized Landing for Small and Micro UAS

  2026-01-08

  articleSenior author

  This paper develops an approach to landing small uncrewed multirotors on inclined surfaces via backwards reachable sets. It is assumed that upon contact the vehicle's ``foot'' does not slip and is modeled as a pin joint. The backward computation has three stages: (1) beginning with the vehicle stationary with all feet on the landing surface, conservation of energy is used to compute the set of feasible vehicle states immediately post contact that result in safe landing; (2) conservation of momentum is then used to determine the pre-contact set of vehicle states that lead to the safe post-contact states; (3) finally kinematics is used to determine the trigger states: the set of that result in safe pre-contact states assuming a particular landing maneuver. This set of safe states and trigger maneuver is then tested in a higher order simulation and compared with a landing policy computed using reinforcement learning. The comparison shows that the low order approach successfully computes a landing policy for arbitrarily inclined landing surfaces and that higher order dynamics (such as impact dynamics and leg flexibility) are critical at the boundaries of the safe landing set but do not adversely affect landings triggered from near the centroid of the safe landing set.

  PublisherDOI

• Ship Deck Tracking in High Sea States via Distributed Estimation

  2026-01-08

  articleSenior author

  Safe and reliable landing of autonomous UAS on moving maritime platforms poses a significant challenge. This paper presents a decentralized and distributed extended information filter for ship deck state estimation and landing by cooperative UAS. Each UAS estimates the relative pose of the ship using fiducial markers and computer vision, combined with a second-order kinematic model of the ship, fused in the information filter. Algorithm performance and functionality are evaluated in a simulation environment that models different sea states using a two-dimensional directional Pierson-Moskowitz ocean spectrum and a ship dynamic model (so that dynamics that are not modeled in the information filter are in the simulated ship model). The simulation tests several deck state scenarios, including cooperative and evasive ship behavior. The filter is initialized based on anticipated sea conditions and the assumed cooperativeness of the ship during the mission. The algorithm leads to accurate deck state estimates both under full-rate communication and during intermittent communication losses among UAS.

  PublisherDOI

• Characterizing Observer Sense of Safety When Witnessing Complex Aircraft Trajectories

  2025-07-16

  article

  As the number of unmanned aerial vehicles (UAVs) in low-altitude missions is increasing, it becomes crucial to ensure that people feel safe under that air space and as passengers on aircraft. Ideally, UAVs should operate in a manner that is both safe and predictable to non-expert human observers. This study examines how people rate airspace safety and collision likelihood when witnessing simulated UAV aircraft trajectories of varying complexity. Participants rated each scenario based on their perception of the likelihood of collision (PLC) and sense of safety (SoS), providing insights into how humans assess flight safety as both passengers inside an aircraft and ground observers. The results reveal important aspects of human safety perception while witnessing crowded airspaces. Observers on the ground report feeling less safe compared to those inside the aircraft, highlighting the influence of perspective on safety perception. Furthermore, the complexity of UAV trajectories does not linearly correlate with perceived safety; instead, curved trajectories such as sinusoidal and looped paths are particularly associated with a decreased sense of safety when viewed from the ground. These findings suggest that human observers struggle to accurately assess safety in complex flight scenarios, emphasizing the need for UAV designers to consider how people will view the vehicle's behavior.

  PublisherDOI

• Design and Initial Flight Testing of a Coaxial Tilting-Head Compound Rotorcraft

  2024-05-07

  articleSenior author

  This paper describes the design and initial flight testing of a compound coaxial tilting head rotorcraft (CCT-HR). Control is provided by titling the rotor head for roll and pitch, differential rotor speed for yaw rate, and rotor speed for total thrust. In addition, a longitudinal thruster is incorporated to enable higher speed forward flight and to add a degree of freedom for longitudinal trim in forward flight. The intent is to explore the feasibility of this vehicle concept and to develop a vehicle that can be used to explore control strategies. The steady state flight envelope is developed analytically; a simulation of longitudinal degrees of freedom is described and a control method for forward flight that incorporates the thruster is proposed. Results of near-hover flight tests are described and initial tests of forward flight using the thruster are described. The vehicle is shown to be stable and easily controllable near hover; in thruster-powered forward flight unmodeled rotor dynamics result in instability.

  PublisherDOI

• UAS data retrieval for large sensor networks

  2024-01-04

  articleSenior author

  This paper examines data retrieval from a network of distributed sensors using an electrically powered uncrewed aircraft system (UAS) under the assumption that it is not possible to visit all sensors in a single flight and therefore multiple flights will be required (a resource constrained travelling salesman problem with refueling, RCTSP-R). Two aspects of this problem are addressed: first, minimizing the total time required to charge the UAS and complete a flight and second, finding a good solution to the resource constrained TSP with refueling. Time minimization is shown to be equivalent to the final glide problem in soaring and a sectoring-based approach is proposed to solve the resource constrained TSP with refueling. Monte Carlo simulations are used to show the utility of the proposed approaches, including the effects of wind on energy required for flight.

  PublisherDOI

• Model-Scale Evaluation of Autonomous Ship Landing Guidance and Control Modes

  Journal of the American Helicopter Society · 2024-01-03 · 4 citations

  article

  This paper presents the results of an extensive model-scale experimental evaluation of autonomous ship landing guidance and control modes, with flight tests performed in the Maneuvering and Seakeeping (MASK) Basin at the U.S. Naval Surface Warfare Center Carderock Division. The experiments were performed using a commodities-based multirotor unmanned aerial vehicle (UAV) operating from a 20-ft-long model scale ship subject to scaled wave conditions. During testing, two separate guidance algorithms were evaluated: a quadratic programming (QP) based landing algorithm that plans the trajectory to a forecasted deck state and a simpler “baseline??? method that tracks deck motions while closing the distance between the aircraft and deck at a constant rate. Both algorithms commanded a Froude-scaled explicit model following control law, and the control law parameters were modified to progressively degrade aircraft tracking bandwidths. The results showed that the predictive capabilities of the QP algorithm allowed more direct landing paths to be planned when compared to the baseline algorithm and also allowed the QP algorithm to land with lower tracking bandwidths. But while the QP algorithm performed well in the majority of cases, there were several landings where a combination of poor deck state predictions and how the QP algorithm utilizes predictions to choose a land time resulted in significant terminal velocity and attitude errors. The baseline guidance algorithm, on the other hand, proved to be both simple and reliable when the UAV was in high bandwidth configurations but required a high reference tracking bandwidth.

  PublisherDOI

• Human Perception of Collision and Safety in Densely Populated Airspaces

  Journal of Aerospace Information Systems · 2024-12-17

  article

  In the very near future, our skies may be occupied with various types of Unmanned Aerial Vehicles (UAVs) assigned with low-altitude missions. Given that uncrewed and crewed aircraft are expected to share the same airspace, addressing passenger perceptions of UAVs is crucial for maintaining confidence in air travel safety. Autonomous and remotely piloted UAVs operating in a human-integrated dense airspace must operate in a manner that is both safe and easily predictable by human observers. In this study, simulations of various UAV collision-avoidance scenarios were generated, which were then used to produce realistic video clips representing the scenarios. Human participants were then asked to rate the scenarios in terms of their perception of likelihood of collision and sense of safety. These ratings were used to assess the accuracy of human perception of near collisions and flight safety, both as a passenger inside an aircraft and as a ground observer. The results highlight some important trends in human perception of safety in the airspace. Human observers feel less safe when observing the airspace from the ground compared to being inside an aircraft. They also feel more unsafe in the presence of uncooperative aircraft in the airspace.

  PublisherDOI

• Flight Path Planning for Minimization of Total Noise Exposure in Urban Air Mobility Operations

  2024-01-04 · 3 citations

  article

  Noise generated by rotorcraft is a major barrier to the acceptance and integration of Urban Air Mobility (UAM) operations in populated areas. Annoyance due to rotorcraft noise increases with the noise level as well as the total duration and frequency of exposure. As such, noise annoyance serves as an important metric for the impact of Urban Air Mobility operations. This paper presents a method for the mitigation of noise for distributed grounded observers through path planning, using sound exposure as a proxy metric for annoyance. In the method presented herein, optimal vehicle flight paths are obtained individually using the A* grid-based optimal pathfinding method, with a cost function based on existing local area sound exposure and local area background noise levels. Optimal grid-based path generation and simulation of vehicle flight trajectories with persistent noise between flights enables global minimization of total and peak sound exposure for multiple aircraft. The proposed method serves as a simulation framework for future works with alternative models of annoyance, ambient soundscape, cost weighting, and vehicle dynamics and acoustics.

  PublisherDOI

Recent grants

• CAREER: Theory and Practice of Autonomous Soaring for Aerial Robots

  NSF · $446k · 2008–2014

• RI: Medium: Collaborative Research: Towards Perpetual Flight of a Gliding Unmanned Aerial Vehicle in the Jet Stream

  NSF · $242k · 2011–2015

Frequent coauthors

• Joseph F. Horn

  Pennsylvania State University

  11 shared

• John J. Bird

  The University of Texas at El Paso

  9 shared

• Sven Schmitz

  Pennsylvania State University

  9 shared

• André Desbiens

  9 shared

• R. D. Lorenz

  9 shared

• Andre Michelin

  University of California, Los Angeles

  9 shared

• Carole G. Prévost

  9 shared

• Jason L. Speyer

  University of California, Los Angeles

  9 shared

Labs

• Vertical Lift and Rotorcraft Center of Excellence (VLRCOE)PI

Education

• Ph.D., Aeronautics and Astronautics

  Stanford University

  2006

Awards & honors

• AIAA Aero Acoustics Award (3)
• AIAA Sperry Award (2)
• AIAA Applied Aerodynamics Award
• Am Astronautical Society Brouwer Award
• AIAA de Florez Award in Flight Simulation