Simultaneous Navigation and Construction Benchmarking Environments
收藏arXiv2021-03-31 更新2024-06-21 收录
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https://ai4ce.github.io/SNAC/
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资源简介：
Simultaneous Navigation and Construction Benchmarking Environments（SNAC）是由纽约大学创建的一个用于评估机器人在移动构造任务中性能的数据集。该数据集旨在解决机器人在无GPS环境下，同时进行定位和环境操作的挑战。SNAC通过简化环境动态和感知模型，设计了一系列移动构造任务，以推动智能移动构造机器人的发展。数据集涵盖了从1D到3D的不同维度网格世界，用于测试和比较不同算法在机器人定位、规划和学习方面的性能。
Simultaneous Navigation and Construction Benchmarking Environments (SNAC) is a dataset developed by New York University for evaluating robotic performance in mobile construction tasks. This dataset addresses the challenge of robots performing simultaneous localization and environmental manipulation in GPS-denied environments. SNAC designs a series of mobile construction tasks by simplifying environmental dynamics and perception models, so as to advance the development of intelligent mobile construction robots. The dataset covers grid worlds with dimensions ranging from 1D to 3D, which are used to test and compare the performance of different algorithms in robotic localization, planning and learning.
提供机构：
纽约大学
创建时间：
2021-03-31
