Dataset Dynamic Continuum Robot

Andrea Gotelli's dataset provides synchronized multi-sensor measurements from a tendon-driven continuum robot. It includes raw and processed data from quasi-static and dynamic motions, including contact scenarios, across planar, circular, and Lissajous trajectories. The 4.8 GB collection, last updated in April 2026, is structured for machine readability and includes cross-validation procedures for data consistency.

Use Cases

• Benchmarking dynamic models based on synchronized kinematics and actuation state data
• Developing data-driven control methods based on multi-sensor recordings of robot trajectories
• Analyzing contact behavior based on interaction force and motion data
• Researching sensor fusion techniques based on cross-validated measurements from multiple modalities

Strengths

• Includes both raw sensor recordings and processed data (filtered, time-aligned, resampled)
• Performs cross-validation across sensing modalities for internal consistency
• Data is provided in structured, machine-readable formats (CSV, MAT, TXT, etc.)
• Covers multiple motion types (planar, circular, Lissajous) at different speeds and contact scenarios

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment

Provenance

Source

Andrea Gotelli via figshare

Collection Method

Experimental measurements from a tendon-driven continuum robot undergoing controlled motions.

Time Range

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Freshness

Last updated 2026-04-12 19:48:59

Geography

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