Related papers: LiC Detector Toy - Tracking detector optimization …
Simulation is central to the evaluation of intelligent transportation system (ITS) applications. As ITS increasingly incorporates autonomous vehicle (AV) technologies as fleet vehicles and/or mobile sensors, accurate modeling of their…
The Inner Tracking System (ITS) Upgrade for the ALICE experiment at LHC is the first large-area ($\sim$10~m$^2$) silicon vertex detector based on the CMOS Monolithic Active Pixel Sensor (MAPS) technology, which combines sensitive volume and…
With the rapid proliferation of autonomous driving, there has been a heightened focus on the research of lidar-based 3D semantic segmentation and object detection methodologies, aiming to ensure the safety of traffic participants. In recent…
ATLAS is making extensive efforts towards preparing a detector upgrade for the high luminosity operations of the LHC (HL-LHC), which will commence operation in about 10 years. The current ATLAS Inner Detector will be replaced by an…
We summarize the R&D activities on a novel semitransparent microstrip sensor to be used on laser-based alignment systems for silicon trackers. The new sensor is used both for particle tracking and laser detection. The aim of this research…
We propose a demonstration-efficient strategy to compress a computationally expensive Model Predictive Controller (MPC) into a more computationally efficient representation based on a deep neural network and Imitation Learning (IL). By…
Subatomic particle track reconstruction (tracking) is a vital task in High-Energy Physics experiments. Tracking is exceptionally computationally challenging and fielded solutions, relying on traditional algorithms, do not scale linearly.…
Fast, incremental evolution of physics instrumentation raises the question of efficient software abstraction and transferability of algorithms across similar technologies. This contribution aims to provide an answer by introducing Track…
Visual tracking fundamentally involves regressing the state of the target in each frame of a video. Despite significant progress, existing regression-based trackers still tend to experience failures and inaccuracies. To enhance the…
Urban-oriented autonomous vehicles require a reliable perception technology to tackle the high amount of uncertainties. The recently introduced compact 3D LIDAR sensor offers a surround spatial information that can be exploited to enhance…
This paper studies data-driven iterative learning control (ILC) for linear time-invariant (LTI) systems with unknown dynamics, output disturbances and input box-constraints. Our main contributions are: 1) using a non-parametric data-driven…
The physics aims at the proposed high-energy $e^+e^-$ collider CLIC pose challenging demands on the performance of the detector system. Precise hit-time tagging, an excellent spatial resolutions, and a low mass are required for the vertex…
Learning to perform perfect tracking tasks based on measurement data is desirable in the controller design of systems operating repetitively. This motivates the present paper to seek an optimization-based design approach for iterative…
The ALICE collaboration is preparing an upgrade of the three innermost layers of the current Inner Tracking System (ITS) during the next LHC long shutdown (LS3). The new ITS detector will use wafer-scale (up to \SI{27}{cm} in length)…
The International Large Detector (ILD) is a concept for a detector at the International Linear Collider, ILC. The ILC will collide electrons and positrons at energies of initially 500 GeV, upgradeable to 1 TeV. The ILC has an ambitious…
In currently available literature, no tracking-by-detection (TBD) paradigm-based tracking method has considered the localization confidence of detection boxes. In most TBD-based methods, it is considered that objects of low detection…
The multi-state constraint Kalman filter (MSCKF) has been proven to be more efficient than graph optimization for visual-based odometry while with similar accuracy. However, it has not been adequately considered and studied for LiDAR-based…
This paper aims for high-performance offline LiDAR-based 3D object detection. We first observe that experienced human annotators annotate objects from a track-centric perspective. They first label the objects with clear shapes in a track,…
The ILD detector is proposed for an electron-positron collider with collision centre-of-mass energies from 90~\GeV~to about 1~\TeV. It has been developed over the last 10 years by an international team of scientists with the goal to design…
Real-time object tracking necessitates a delicate balance between speed and accuracy, a challenge exacerbated by the computational demands of deep learning methods. In this paper, we propose Confidence-Triggered Detection (CTD), an…