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Path planning is a crucial algorithmic approach for designing robot behaviors. Sampling-based approaches, like rapidly exploring random trees (RRTs) or probabilistic roadmaps, are prominent algorithmic solutions for path planning problems.…
Differentiable ARchiTecture Search, i.e., DARTS, has drawn great attention in neural architecture search. It tries to find the optimal architecture in a shallow search network and then measures its performance in a deep evaluation network.…
Network intrusion detection systems (NIDSs) play an important role in computer network security. There are several detection mechanisms where anomaly-based automated detection outperforms others significantly. Amid the sophistication and…
Chinese Spallation Neutron Source (CSNS), one project of the 12th five-year-plan scheme of China, is under construction in Guangdong province. Three neutron spectrometers will be installed at the first phase of the project, where…
Benefiting from its ability to efficiently learn how an object is changing, correlation filters have recently demonstrated excellent performance for rapidly tracking objects. Designing effective features and handling model drifts are two…
In this work, we present a novel robust distributed beamforming (RDB) approach to mitigate the effects of channel errors on wireless networks equipped with relays based on the exploitation of the cross-correlation between the received data…
Integrable optics is an innovation in particle accelerator design that potentially enables a greater betatron tune spread and damps collective instabilities. An integrable rapid-cycling synchrotron (RCS) would be an effective replacement…
A reliable odometry source is a prerequisite to enable complex autonomy behaviour in next-generation robots operating in extreme environments. In this work, we present a high-precision lidar odometry system to achieve robust and real-time…
Recently, the joint design of optical systems and downstream algorithms is showing significant potential. However, existing rays-described methods are limited to optimizing geometric degradation, making it difficult to fully represent the…
Discrete optimization is a central problem in mathematical optimization with a broad range of applications, among which binary optimization and sparse optimization are two common ones. However, these problems are NP-hard and thus difficult…
The contribution of this paper is the application of compound state-triggered constraints (STCs) to real-time quad-rotor path planning. Originally developed for rocket landing applications, STCs are made up of a trigger condition and a…
This work studies the problem of radar detection of correlated gamma-fluctuating targets in the presence of clutter described by compound models with correlated speckle. If the correlation is not accounted for in a radar model, the required…
Distributed optimization consists of multiple computation nodes working together to minimize a common objective function through local computation iterations and network-constrained communication steps. In the context of robotics,…
In this work, we introduce a new design concept: the DC-Coupled Resistive Silicon Detectors, based on the LGAD technology. This new approach intends to address a few known features of the first generation of AC-Coupled Resistive Silicon…
For many next-generation high intensity proton accelerator applications including the Spallation Neutron Source (SNS), superconducting (SC) RF provides the technology of choice for the linac. In designing the superconducting cavity, several…
Integrable optics is an innovation in particle accelerator design that provides strong nonlinear focusing while avoiding parametric resonances. One promising application of integrable optics is to overcome the traditional limits on…
This paper proposes a scalable channel estimation and reflection optimization framework for reconfigurable intelligent surface (RIS)-enhanced orthogonal frequency division multiplexing (OFDM) systems. Specifically, the proposed scheme…
There have been significant advances in neural networks for both 3D object detection using LiDAR and 2D object detection using video. However, it has been surprisingly difficult to train networks to effectively use both modalities in a way…
In this paper, we present a concurrent and scalable trajectory optimization method to improve the quality of robot-assisted manufacturing. Our method simultaneously optimizes tool orientations, kinematic redundancy, and waypoint timing on…
In this paper, we present a parallel computing method for the coupled-cluster singles and doubles (CCSD) in periodic systems. The CCSD in periodic systems solves simultaneous equations for single-excitation and double-excitation amplitudes.…