Zobrazeno 1 - 10
of 156
pro vyhledávání: '"Skrzypczyński Piotr"'
Publikováno v:
International Journal of Applied Mathematics and Computer Science, Vol 32, Iss 4, Pp 583-599 (2022)
We present a novel approach to vision-based localization of electric city buses for assisted docking to a charging station. The method assumes that the charging station is a known object, and employs a monocular camera system for positioning upon car
Externí odkaz:
https://doaj.org/article/3663c97a2b0d4802a1f1832618b57399
Autor:
Banaszczyk, Adam, Łysakowski, Mikołaj, Nowicki, Michał R., Skrzypczyński, Piotr, Tadeja, Sławomir K.
Publikováno v:
2024 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)
In this paper, we introduce a new methodology for assessing the positioning accuracy of virtual reality (VR) headsets, utilizing a cooperative industrial robot to simulate user head trajectories in a reproducible manner. We conduct a comprehensive ev
Externí odkaz:
http://arxiv.org/abs/2412.06116
Autor:
Skrzypczyński Piotr, Kornuta Tomasz
Publikováno v:
Foundations of Computing and Decision Sciences, Vol 42, Iss 3, Pp 179-182 (2017)
Externí odkaz:
https://doaj.org/article/997bd632403249d6b7aea7dde69387f7
Publikováno v:
International Journal of Applied Mathematics and Computer Science, Vol 26, Iss 1, Pp 63-79 (2016)
The problem of position and orientation estimation for an active vision sensor that moves with respect to the full six degrees of freedom is considered. The proposed approach is based on point features extracted from RGB-D data. This work focuses on
Externí odkaz:
https://doaj.org/article/e43d7facaeeb43ab9afafef088514030
Real-Time Onboard Object Detection for Augmented Reality: Enhancing Head-Mounted Display with YOLOv8
Autor:
Łysakowski, Mikołaj, Żywanowski, Kamil, Banaszczyk, Adam, Nowicki, Michał R., Skrzypczyński, Piotr, Tadeja, Sławomir K.
This paper introduces a software architecture for real-time object detection using machine learning (ML) in an augmented reality (AR) environment. Our approach uses the recent state-of-the-art YOLOv8 network that runs onboard on the Microsoft HoloLen
Externí odkaz:
http://arxiv.org/abs/2306.03537
Reproducibility is one of the core dimensions that concur to deliver Trustworthy Artificial Intelligence. Broadly speaking, reproducibility can be defined as the possibility to reproduce the same or a similar experiment or method, thereby obtaining t
Externí odkaz:
http://arxiv.org/abs/2302.12691
Autor:
Kicki, Piotr, Liu, Puze, Tateo, Davide, Bou-Ammar, Haitham, Walas, Krzysztof, Skrzypczyński, Piotr, Peters, Jan
Motion planning is a mature area of research in robotics with many well-established methods based on optimization or sampling the state space, suitable for solving kinematic motion planning. However, when dynamic motions under constraints are needed
Externí odkaz:
http://arxiv.org/abs/2301.04330
Although haptic sensing has recently been used for legged robot localization in extreme environments where a camera or LiDAR might fail, the problem of efficiently representing the haptic signatures in a learned prior map is still open. This paper in
Externí odkaz:
http://arxiv.org/abs/2209.15135
Autor:
Kicki, Piotr, Skrzypczyński, Piotr
This paper demonstrates how an efficient representation of the planned path using B-splines, and a construction procedure that takes advantage of the neural network's inductive bias, speed up both the inference and training of a DNN-based motion plan
Externí odkaz:
http://arxiv.org/abs/2203.06963
We propose an extension to the segment-based global localization method for LiDAR SLAM using descriptors learned considering the visual context of the segments. A new architecture of the deep neural network is presented that learns the visual context
Externí odkaz:
http://arxiv.org/abs/2108.01383