5 papers
Environment-Aware Learning of Smooth GNSS Covariance Dynamics for Autonomous Racing
Y. Deemo Chen, Arion Zimmermann, Thomas A. Berrueta +1
Ensuring accurate and stable state estimation is a challenging task crucial to safety-critical domains such as high-speed autonomous racing, where measurement uncertainty must be b…
MonoTher-Depth: Enhancing Thermal Depth Estimation via Confidence-Aware Distillation
Xingxing Zuo, Nikhil Ranganathan, Connor Lee +2
Monocular depth estimation (MDE) from thermal images is a crucial technology for robotic systems operating in challenging conditions such as fog, smoke, and low light. The limited…
Monte Carlo Tree Search with Spectral Expansion for Planning with Dynamical Systems
Benjamin Riviere, John Lathrop, Soon-Jo Chung
The ability of a robot to plan complex behaviors with real-time computation, rather than adhering to predesigned or offline-learned routines, alleviates the need for specialized al…
Motor Imagery Teleoperation of a Mobile Robot Using a Low-Cost Brain-Computer Interface for Multi-Day Validation
Yujin An, Daniel Mitchell, John Lathrop +2
Brain-computer interfaces (BCI) have the potential to provide transformative control in prosthetics, assistive technologies (wheelchairs), robotics, and human-computer interfaces.…
Model Predictive Trees: Sample-Efficient Receding Horizon Planning with Reusable Tree Search
John Lathrop, Benjamin Rivi`ere, Jedidiah Alindogan +1
We present Model Predictive Trees (MPT), a receding horizon tree search algorithm that improves its performance by reusing information efficiently. Whereas existing solvers reuse o…