Zobrazeno 1 - 10
of 299
pro vyhledávání: '"Barfoot, Timothy D"'
Autor:
Talbot, William, Nubert, Julian, Tuna, Turcan, Cadena, Cesar, Dümbgen, Frederike, Tordesillas, Jesus, Barfoot, Timothy D., Hutter, Marco
Accurate, efficient, and robust state estimation is more important than ever in robotics as the variety of platforms and complexity of tasks continue to grow. Historically, discrete-time filters and smoothers have been the dominant approach, in which
Externí odkaz:
http://arxiv.org/abs/2411.03951
How can a robot safely navigate around people exhibiting complex motion patterns? Reinforcement Learning (RL) or Deep RL (DRL) in simulation holds some promise, although much prior work relies on simulators that fail to precisely capture the nuances
Externí odkaz:
http://arxiv.org/abs/2410.10646
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 using a novel Gaussian-process prior that is parameterized over both arcl
Externí odkaz:
http://arxiv.org/abs/2409.12302
A key element of many odometry pipelines using spinning frequency-modulated continuous-wave (FMCW) radar is the extraction of a point-cloud from the raw signal. This extraction greatly impacts the overall performance of point-cloud-based odometry. Th
Externí odkaz:
http://arxiv.org/abs/2409.12256
Frequency-modulated continuous-wave (FMCW) scanning radar has emerged as an alternative to spinning LiDAR for state estimation on mobile robots. Radar's longer wavelength is less affected by small particulates, providing operational advantages in cha
Externí odkaz:
http://arxiv.org/abs/2409.10491
We present closed-form expressions for marginalizing and conditioning Gaussians onto linear manifolds, and demonstrate how to apply these expressions to smooth nonlinear manifolds through linearization. Although marginalization and conditioning onto
Externí odkaz:
http://arxiv.org/abs/2409.09871
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 identifies objects of interest in LiDAR keyframes, refines their 3D poses wi
Externí odkaz:
http://arxiv.org/abs/2408.17034
Autor:
Lilge, Sven, Barfoot, Timothy D.
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-motivated priors have been considered for such approaches, using assumpt
Externí odkaz:
http://arxiv.org/abs/2408.01333
In recent years, many estimation problems in robotics have been shown to be solvable to global optimality using their semidefinite relaxations. However, the runtime complexity of off-the-shelf semidefinite programming (SDP) solvers is up to cubic in
Externí odkaz:
http://arxiv.org/abs/2406.02365
Differentiable optimization is a powerful new paradigm capable of reconciling model-based and learning-based approaches in robotics. However, the majority of robotics optimization problems are non-convex and current differentiable optimization techni
Externí odkaz:
http://arxiv.org/abs/2405.19309