A tutorial on quantitative trajectory evaluation for visual (-inertial) odometry

Z Zhang, D Scaramuzza - 2018 IEEE/RSJ International …, 2018 - ieeexplore.ieee.org
In this tutorial, we provide principled methods to quantitatively evaluate the quality of an
estimated trajectory from visual (-inertial) odometry (VO/VIO), which is the foundation of …

[HTML][HTML] Integrated trajectory estimation for 3D kinematic mapping with GNSS, INS and imaging sensors: A framework and review

F Pöppl, H Neuner, G Mandlburger, N Pfeifer - ISPRS Journal of …, 2023 - Elsevier
Trajectory estimation refers to the task of obtaining position and orientation estimates by
fusing various sensor inputs. In kinematic mapping, global navigation satellite systems …

Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age

C Cadena, L Carlone, H Carrillo, Y Latif… - IEEE Transactions …, 2016 - ieeexplore.ieee.org
Simultaneous localization and mapping (SLAM) consists in the concurrent construction of a
model of the environment (the map), and the estimation of the state of the robot moving …

Continuous-time Gaussian process motion planning via probabilistic inference

M Mukadam, J Dong, X Yan… - … Journal of Robotics …, 2018 - journals.sagepub.com
We introduce a novel formulation of motion planning, for continuous-time trajectories, as
probabilistic inference. We first show how smooth continuous-time trajectories can be …

Motion planning diffusion: Learning and planning of robot motions with diffusion models

J Carvalho, AT Le, M Baierl, D Koert… - 2023 IEEE/RSJ …, 2023 - ieeexplore.ieee.org
Learning priors on trajectory distributions can help accelerate robot motion planning
optimization. Given previously successful plans, learning trajectory generative models as …

Decentralized active information acquisition: Theory and application to multi-robot SLAM

N Atanasov, J Le Ny, K Daniilidis… - 2015 IEEE International …, 2015 - ieeexplore.ieee.org
This paper addresses the problem of controlling mobile sensing systems to improve the
accuracy and efficiency of gathering information autonomously. It applies to scenarios such …

Continuum robot state estimation using gaussian process regression on se (3)

S Lilge, TD Barfoot… - The International Journal …, 2022 - journals.sagepub.com
Continuum robots have the potential to enable new applications in medicine, inspection,
and countless other areas due to their unique shape, compliance, and size. Excellent …

Active observing in continuous-time control

S Holt, A Hüyük… - Advances in Neural …, 2024 - proceedings.neurips.cc
The control of continuous-time environments while actively deciding when to take costly
observations in time is a crucial yet unexplored problem, particularly relevant to real-world …

Do we need to compensate for motion distortion and doppler effects in spinning radar navigation?

K Burnett, AP Schoellig… - IEEE Robotics and …, 2021 - ieeexplore.ieee.org
In order to tackle the challenge of unfavorable weather conditions such as rain and snow,
radar is being revisited as a parallel sensing modality to vision and lidar. Recent works have …

[PDF][PDF] Motion planning as probabilistic inference using Gaussian processes and factor graphs.

J Dong, M Mukadam, F Dellaert… - Robotics: Science and …, 2016 - homes.cs.washington.edu
With the increased use of high degree-of-freedom robots that must perform tasks in real-
time, there is a need for fast algorithms for motion planning. In this work, we view motion …