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Description
WheelArm is a real-robot dataset collected from a Kinova Gen3 6-DOF manipulator arm mounted on a powered wheelchair. Each episode captures a single assistive daily-living task performed by a human operator. The dataset includes synchronized RGB video, depth, robot kinematics, audio, and natural-language dialogue with ambiguity annotations.
Use Cases
Train multimodal models for robot task understanding based on synchronized video, depth, and kinematics.
Develop dialogue systems for assistive robots based on the natural-language dialogue annotations.
Study human-robot interaction and task ambiguity using the provided annotations.
Benchmark robot learning algorithms for daily-living tasks using real-world demonstrations.
Strengths
Dataset includes synchronized multimodal streams: RGB video, depth, robot kinematics, audio, and dialogue.
Data is collected from a real Kinova Gen3 6-DOF manipulator on a powered wheelchair.
Episodes are focused on assistive daily-living tasks performed by a human operator.
Limitations
Column-level documentation is absent; field semantics must be inferred after download.
Row count is unknown, which may limit suitability assessment.
Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
Source
huggingface
Collection Method
Collected from a real-robot setup with a Kinova Gen3 arm on a powered wheelchair.
Freshness
Last updated 2026-05-20 16:43:35; freshness should be verified.
License is unknown; terms of use must be verified before application.