no code implementations • 12 Oct 2023 • Minh Q. Ta, Holly Dinkel, Hameed Abdul-Rashid, Yangfei Dai, Jessica Myers, Tan Chen, Junyi Geng, Timothy Bretl
This work evaluates the impact of time step frequency and component scale on robotic manipulation simulation accuracy.
no code implementations • 15 Sep 2023 • Jongwon Lee, Su Yeon Choi, Timothy Bretl
This paper quantifies the performance of visual SLAM that leverages multi-scale fiducial markers (i. e., artificial landmarks that can be detected at a wide range of distances) to show its potential for reliable takeoff and landing navigation in rotorcraft.
no code implementations • 8 Sep 2023 • Jongwon Lee, Su Yeon Choi, David Hanley, Timothy Bretl
This paper presents a comparative study of three modes for mobile robot localization based on visual SLAM using fiducial markers (i. e., square-shaped artificial landmarks with a black-and-white grid pattern): SLAM, SLAM with a prior map, and localization with a prior map.
2 code implementations • 27 May 2023 • Ehsan Saleh, Saba Ghaffari, Timothy Bretl, Luke Olson, Matthew West
Our numerical results confirm the existence of the aforementioned bias in practice, and also show that our proposed delayed target approach can lead to accurate solutions with comparable quality to ones estimated with a large number of samples.
no code implementations • 9 Oct 2022 • James Motes, Tan Chen, Timothy Bretl, Marco Morales, Nancy M. Amato
We present a multi-robot task and motion planning method that, when applied to the rearrangement of objects by manipulators, results in solution times up to three orders of magnitude faster than existing methods and successfully plans for problems with up to twenty objects, more than three times as many objects as comparable methods.
1 code implementation • 30 May 2022 • Ehsan Saleh, Saba Ghaffari, Timothy Bretl, Matthew West
In this paper, we present a policy gradient method that avoids exploratory noise injection and performs policy search over the deterministic landscape.
1 code implementation • 31 Dec 2021 • Xinke Deng, Junyi Geng, Timothy Bretl, Yu Xiang, Dieter Fox
The auto-encoder can be used in a particle filter framework to estimate and track 6D poses of objects in a category.
3 code implementations • 23 Sep 2019 • Xinke Deng, Yu Xiang, Arsalan Mousavian, Clemens Eppner, Timothy Bretl, Dieter Fox
In this way, our system is able to continuously collect data and improve its pose estimation modules.
Robotics
1 code implementation • 22 May 2019 • Xinke Deng, Arsalan Mousavian, Yu Xiang, Fei Xia, Timothy Bretl, Dieter Fox
In this work, we formulate the 6D object pose tracking problem in the Rao-Blackwellized particle filtering framework, where the 3D rotation and the 3D translation of an object are decoupled.
no code implementations • ECCV 2018 • Joseph DeGol, Timothy Bretl, Derek Hoiem
In this paper, we present an incremental structure from motion (SfM) algorithm that signiï¬cantly outperforms existing algorithms when ï¬ducial markers are present in the scene, and that matches the performance of existing algorithms when no markers are present.
no code implementations • ICCV 2017 • Joseph DeGol, Timothy Bretl, Derek Hoiem
Current fiducial marker detection algorithms rely on marker IDs for false positive rejection.