智能仿生无人系统核心算法数据集

“智能仿生无人系统核心算法数据集”主要面向智能仿生无人系统的算法研发与仿真验证研究需求建设，基于北京科技大学研究团队于2024年3月至2025年5月期间在北京完成的仿真实验与实物测试数据生成。数据采集与处理在Lenovo Legion R9000k计算平台上完成，运行环境包括PyTorch、MATLAB与ROS。本数据集系统汇集了仿生无人系统在视觉感知与飞行控制领域的核心算法数据，涵盖目标检测、目标跟踪、目标定位、姿态控制、飞控系统辨识及集群控制六类算法。数据包括算法说明文档（.docx）、算法源代码（.py、.mat）、仿真与实测运行结果文件（.png、.xlsx）等内容。数据集以“算法-仿真-验证”一体化流程构建，既包含深度学习训练数据与模型文件，也记录了不同实验条件下算法运行过程的关键数值与可视化结果，形成了智能仿生无人系统算法层面的完整支撑体系。该数据集为仿生无人系统的智能感知、控制决策与多机协同研究提供了基础数据与验证依据，对推动自主无人系统算法研发与技术创新具有重要意义。数据总量约365MB。

Core Algorithm Dataset for Intelligent Bionic Unmanned Systems is constructed to meet the research needs of algorithm development and simulation verification for intelligent bionic unmanned systems. It is generated from simulation experiment and physical test data completed by the research team of University of Science and Technology Beijing from March 2024 to May 2025 in Beijing. Data collection and processing were carried out on the Lenovo Legion R9000k computing platform, with operating environments including PyTorch, MATLAB and ROS. This dataset collects core algorithm data of bionic unmanned systems in the fields of visual perception and flight control, covering six types of algorithms: target detection, target tracking, target positioning, attitude control, flight control system identification and swarm control. The data includes algorithm documentation (.docx), algorithm source codes (.py, .mat), simulation and actual measurement operation result files (.png, .xlsx) and other contents. The dataset is constructed through the integrated process of "algorithm-simulation-verification". It not only includes deep learning training data and model files, but also records key values and visualization results of the algorithm operation process under different experimental conditions, forming a complete support system at the algorithm level for intelligent bionic unmanned systems. This dataset provides basic data and verification basis for the research of intelligent perception, control decision-making and multi-machine cooperation of bionic unmanned systems, and is of great significance for promoting the algorithm development and technological innovation of autonomous unmanned systems. The total data volume is approximately 365 MB.

搜集汇总

背景与挑战

背景概述

该数据集面向智能仿生无人系统的算法研发与仿真验证需求，由北京科技大学于2024年3月至2025年5月基于仿真与实物测试生成，涵盖目标检测、跟踪、定位、姿态控制、飞控系统辨识及集群控制六类核心算法的文档、源代码和结果文件。其以'算法-仿真-验证'一体化流程构建，包含深度学习训练数据和实验过程记录，形成了算法层面的完整支撑体系，旨在推动自主无人系统的智能感知、控制与协同研究，数据总量约365MB。