S3E: 協調SLAMのためのマルチロボット・マルチモーダルデータセット
S3E: A Multi-Robot Multimodal Dataset for Collaborative SLAM
複数台の地上ロボットが協調してSLAMを行うための、LiDAR・ステレオ画像・IMU・UWBを同期収録した大規模マルチモーダルデータセットを構築し、協調/単体SLAM手法のベンチマークを提供した。
著者: Dapeng Feng, Yuhua Qi, Shipeng Zhong, Zhiqiang Chen, Qiming Chen, Hongbo Chen, Jin Wu, Jun Ma
分類: cs.RO, cs.CV
原文アブストラクト
The burgeoning demand for collaborative robotic systems to execute complex tasks collectively has intensified the research community's focus on advancing simultaneous localization and mapping (SLAM) in a cooperative context. Despite this interest, the scalability and diversity of existing datasets for collaborative trajectories remain limited, especially in scenarios with constrained perspectives where the generalization capabilities of Collaborative SLAM (C-SLAM) are critical for the feasibility of multi-agent missions. Addressing this gap, we introduce S3E, an expansive multimodal dataset. Captured by a fleet of unmanned ground vehicles traversing four distinct collaborative trajectory paradigms, S3E encompasses 13 outdoor and 5 indoor sequences. These sequences feature meticulously synchronized and spatially calibrated data streams, including 360-degree LiDAR point cloud, high-resolution stereo imagery, high-frequency inertial measurement units (IMU), and Ultra-wideband (UWB) relative observations. Our dataset not only surpasses previous efforts in scale, scene diversity, and data intricacy but also provides a thorough analysis and benchmarks for both collaborative and individual SLAM methodologies. For access to the dataset and the latest information, please visit our repository at https://pengyu-team.github.io/S3E.
