Research

Current funded projects:

  • ERI: Wind Field Estimation and Path Planning for Uncrewed Aerial Vehicles in Urban Environments (NSF; 2023-2025, with M. Uddin). This project aims to improve the fundamental understanding of how aerial robots with limited computational capabilities can collaboratively estimate and exploit a complex urban wind field to plan safer and more efficient flight paths.
  • Evaluation of Unmanned Surface Vessel (USV) Technology for Bathymetric Surveying of Inland Environments (NCDOT; 2023-2025). The long-term goal of this research is to improve the capability of NCDOT to efficiently and cost-effectively collect high-quality bathymetric survey data using unmanned surface vessel platforms in inland bodies of water.

Current/Past Sponsors:

research areas

(1) Marine Robotics: Autonomy Algorithms and Control/Design of Novel Platforms

This work focuses improving marine robots through the design of algorithms the enable intelligent behavior and investigation of novel platform for locomotion or sensing.

Autonomy Algorithms (past and ongoing work):

  • Autonomous sensing of a Gaussian spatial process (e.g., bathymetry) with multiple heterogeneous agents [Link]
  • Multi-vehicle cooperative navigation with intermittent aiding: [Link]
  • Adaptive behaviors for passive sonar tracking of multiple surface vessels with an autonomous underwater vehicle: [Link] [Link]
  • Search planning in a large state space with environmentally varying sensor performance: [Link] [Link]

Control and/or Design of Novel Marine Platforms (past and ongoing work):

  • MicroUUV for indoor experimentation [Link]
  • Planar formation control of bio-inspired underwater vehicles: [Link] [Link]
  • Underwater gliders with pneumatic buoyancy control and cylindrical moving mass actuators [Link], [Link], [Link], [Link]

(2) Modeling, Control, and Estimation for Vehicles in Flow-Fields and Disturbances

This research investigates flow-field mapping/estimation and optimization-based control strategies to improve the robustness of atmospheric and ocean vehicles. Enabling vehicle to operate in complex flow-fields can improve robustness, safety, and enlarge the operating envelope of conditions in which they can operate.

Past and ongoing work:

  • Modeling and control of a UAV in a blast pressure wave
  • Batch estimation of a steady, uniform, flow-field from ground velocity and heading measurements [Link]
  • Quadrotor takeoff trajectory optimization aided by wind-sensing infrastructure [Link]
  • Quadrotor flight simulation in a CFD-generated urban wind field [Link]
  • Feasible Dubins paths in the presence of unsteady velocity disturbances: [Link]

(3) Combined Task and Motion Planning for Autonomous Vehicles

This research investigates how autonomous vehicles can jointly optimize the autonomous selection of high-level tasks and low-level vehicle trajectory plans using tools from network science, operations research, robotics, and motion planning. Applications include autonomous data collection or logistics.

Past and ongoing work:

  • UAV-based package delivery optimization considering battery state-of-health
  • Planning visual inspection tours for a 3D Dubins airplane model in an urban environment [Link]
  • Information-theoretic guidance of a quadrotor team to balance mapping and search in an urban environment: [Link]
  • The orbiting Dubins traveling salesman problem (ODTSP): [Link]

(4) Vehicle Trajectory/Path Optimization

This research investigates optimal path planning of aircraft and ocean vehicles using tools from nonlinear optimal control theory or robotics (e.g., sampling-based motion planning). Reference paths are a fundamental component of a guidance, navigation, and control (GNC) system. Optimal path planning generally aims to minimize/maximize some performance criteria such as time, energy, or risk.

Past and ongoing work:

  • Risk-aware path planning around dynamic engagement zones [Link]
  • Maximum kinetic energy paths for gliding flight vehicles
  • Minimum-energy paths in gliding flight: [Link], [Link],
  • Time-optimal trajectories for a Dubins car with variable speed (and turn rate) controls: [Link]