10 papers
RL-Guided PAC-NMPC for Probabilistically-Safe Perception-Based Navigation in Unknown Environments
Adam Polevoy, Dillon Capalongo, Katherine Tang +3
In this paper, we present an approach for combining stochastic nonlinear model predictive control (SNMPC) and reinforcement learning (RL) to enable probabilistically-safe perceptio…
Stratified Topological Autonomy for Long-Range Coordination (STALC)
Cora A. Duggan, Adam Goertz, Adam Polevoy +5
In this paper, we present Stratified Topological Autonomy for Long-Range Coordination (STALC), a hierarchical planning approach for multi-robot coordination in real-world environme…
Dense Fixed-Wing Swarming using Receding-Horizon NMPC
Varun Madabushi, Yocheved Kopel, Adam Polevoy +1
In this paper, we present an approach for controlling a team of agile fixed-wing aerial vehicles in close proximity to one another. Our approach relies on receding-horizon nonlinea…
Multi-Agent Feedback Motion Planning using Probably Approximately Correct Nonlinear Model Predictive Control
Mark Gonzales, Adam Polevoy, Marin Kobilarov +1
For many tasks, multi-robot teams often provide greater efficiency, robustness, and resiliency. However, multi-robot collaboration in real-world scenarios poses a number of major c…
Robust Perception-Based Navigation using PAC-NMPC with a Learned Value Function
Adam Polevoy, Mark Gonzales, Marin Kobilarov +1
Nonlinear model predictive control (NMPC) is typically restricted to short, finite horizons to limit the computational burden of online optimization. As a result, global planning f…
Planning and Control for a Dynamic Morphing-Wing UAV Using a Vortex Particle Model
Gino Perrotta, Luca Scheuer, Yocheved Kopel +4
Achieving precise, highly-dynamic maneuvers with Unmanned Aerial Vehicles (UAVs) is a major challenge due to the complexity of the associated aerodynamics. In particular, unsteady…
Probably Approximately Correct Nonlinear Model Predictive Control (PAC-NMPC)
Adam Polevoy, Marin Kobilarov, Joseph Moore
Approaches for stochastic nonlinear model predictive control (SNMPC) typically make restrictive assumptions about the system dynamics and rely on approximations to characterize the…
Post-Stall Navigation with Fixed-Wing UAVs using Onboard Vision
Adam Polevoy, Max Basescu, Luca Scheuer +1
Recent research has enabled fixed-wing unmanned aerial vehicles (UAVs) to maneuver in constrained spaces through the use of direct nonlinear model predictive control (NMPC). Howeve…
Complex Terrain Navigation via Model Error Prediction
Adam Polevoy, Craig Knuth, Katie M. Popek +1
Robot navigation traditionally relies on building an explicit map that is used to plan collision-free trajectories to a desired target. In deformable, complex terrain, using geomet…
High-Speed Robot Navigation using Predicted Occupancy Maps
Kapil D. Katyal, Adam Polevoy, Joseph Moore +2
Safe and high-speed navigation is a key enabling capability for real world deployment of robotic systems. A significant limitation of existing approaches is the computational bottl…