10 papers
OSCAR: Obstacle Survival Curves for Adaptive Robot Navigation
Hshmat Sahak, Aoran Jiao, Nicholas Rhinehart +1
A mobile robot following a graph of known routes can make costly navigation errors when a temporary obstacle blocks a critical edge: waiting too long behind a parked cart wastes ti…
KILO-EKF: Koopman-Inspired Learned Observations Extended Kalman Filter
Zi Cong Guo, James R. Forbes, Timothy D. Barfoot
We present the Koopman-Inspired Learned Observations Extended Kalman Filter (KILO-EKF), which combines a standard EKF prediction step with a correction step based on a Koopman-insp…
Revisiting Continuous-Time Trajectory Estimation via Gaussian Processes and the Magnus Expansion
Timothy Barfoot, Cedric Le Gentil, Sven Lilge
Continuous-time state estimation has been shown to be an effective means of (i) handling asynchronous and high-rate measurements, (ii) introducing smoothness to the estimate, (iii)…
Ratatouille: Imitation Learning Ingredients for Real-world Social Robot Navigation
James R. Han, Mithun Vanniasinghe, Hshmat Sahak +2
Scaling Reinforcement Learning to in-the-wild social robot navigation is both data-intensive and unsafe, since policies must learn through direct interaction and inevitably encount…
Towards Efficient Occupancy Mapping via Gaussian Process Latent Field Shaping
Cedric Le Gentil, Cedric Pradalier, Timothy D. Barfoot
Occupancy mapping has been a key enabler of mobile robotics. Originally based on a discrete grid representation, occupancy mapping has evolved towards continuous representations th…
Do We Still Need to Work on Odometry for Autonomous Driving?
Cedric Le Gentil, Daniil Lisus, Timothy D. Barfoot
Over the past decades, a tremendous amount of work has addressed the topic of ego-motion estimation of moving platforms based on various proprioceptive and exteroceptive sensors. A…