The YCB-Slide dataset comprises of DIGIT sliding interactions on YCB objects. We envision this can contribute towards efforts in tactile localization, mapping, object understanding, and learning dynamics models. We provide access to DIGIT images, sensor poses, RGB video feed, ground-truth mesh models, and ground-truth heightmaps + contact masks (simulation only). This dataset is supplementary to the MidasTouch paper, a CoRL 2022 submission.
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TorWIC is the dataset discussed in POCD: Probabilistic Object-Level Change Detection and Volumetric Mapping in Semi-Static Scenes. The purpose of this dataset is to evaluate the map mainteneance capabilities in a warehouse environment undergoing incremental changes. This dataset is collected in a Clearpath Robotics facility.
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The Cooperative Driving dataset is a synthetic dataset generated using CARLA that contains lidar data from multiple vehicles navigating simultaneously through a diverse set of driving scenarios. This dataset was created to enable further research in multi-agent perception (cooperative perception) including cooperative 3D object detection, cooperative object tracking, multi-agent SLAM and point cloud registration. Towards that goal, all the frames have been labelled with ground-truth sensor pose and 3D object bounding boxes.
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ConsInv is a stereo RGB + IMU dataset designed for Dynamic SLAM testing and contains two subsets: