38 citations · 50 across the 13 of their papers we have counts for
13 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)…
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…
DR-MPC: Deep Residual Model Predictive Control for Real-world Social Navigation
James R. Han, Hugues Thomas, Jian Zhang +2
How can a robot safely navigate around people with complex motion patterns? Deep Reinforcement Learning (DRL) in simulation holds some promise, but much prior work relies on simula…
Space-Time Continuum: Continuous Shape and Time State Estimation for Flexible Robots
Spencer Teetaert, Sven Lilge, Jessica Burgner-Kahrs +1
This extended abstract introduces a novel method for continuous state estimation of continuum robots. We formulate the estimation problem as a factor-graph optimization problem usi…
MakeWay: Object-Aware Costmaps for Proactive Indoor Navigation Using LiDAR
Binbin Xu, Allen Tao, Hugues Thomas +2
In this paper, we introduce a LiDAR-based robot navigation system, based on novel object-aware affordance-based costmaps. Utilizing a 3D object detection network, our system identi…
Incorporating Control Inputs in Continuous-Time Gaussian Process State Estimation for Robotics
Sven Lilge, Timothy D. Barfoot
Continuous-time batch state estimation using Gaussian processes is an efficient approach to estimate the trajectories of robots over time. In the past, relatively simple physics-mo…
KPConvX: Modernizing Kernel Point Convolution with Kernel Attention
Hugues Thomas, Yao-Hung Hubert Tsai, Timothy D. Barfoot +1
In the field of deep point cloud understanding, KPConv is a unique architecture that uses kernel points to locate convolutional weights in space, instead of relying on Multi-Layer…
GNSS/Multi-Sensor Fusion Using Continuous-Time Factor Graph Optimization for Robust Localization
Haoming Zhang, Chih-Chun Chen, Heike Vallery +1
Accurate and robust vehicle localization in highly urbanized areas is challenging. Sensors are often corrupted in those complicated and large-scale environments. This paper introdu…
Data-Driven Batch Localization and SLAM Using Koopman Linearization
Zi Cong Guo, Frederike Dümbgen, James R. Forbes +1
We present a framework for model-free batch localization and SLAM. We use lifting functions to map a control-affine system into a high-dimensional space, where both the process mod…
Self-Supervised Learning of Lidar Segmentation for Autonomous Indoor Navigation
Hugues Thomas, Ben Agro, Mona Gridseth +2
We present a self-supervised learning approach for the semantic segmentation of lidar frames. Our method is used to train a deep point cloud segmentation architecture without any h…