Autonomous Underwater Vehicle Docking State Transition Simulation Dataset
#World model training #State transition prediction #Next-state prediction #Control tracking analysis #Contact risk assessment #Autonomous underwater vehicles #Underwater docking simulation #Underwater station docking #Marine robot control
- 4750
- 0.5GB
- JSON
- CATL
MOBIUSI INC
Updated:2026-11-03
AI Analysis & Value Prop
This dataset records simulated observations and control actions as an autonomous underwater vehicle approaches a support vessel or underwater station, including relative distance, bearing, closing speed, current-compensated velocity, and communication quality. It covers the docking phases of search, alignment, approach, contact, and disengagement, with state transitions, next-state targets, control tracking errors, and contact risk scores. The data supports world model training, state transition prediction, docking control analysis, and risk assessment.
Dataset Insights
Sample Examples
{}
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| closing_speed | number | Relative closing speed along the line between the vehicle and the target docking interface. |
| control_action | object | Propulsion, attitude, and velocity commands applied to the autonomous underwater vehicle by the controller at the current simulation step. |
| state_transition | object | Docking state transition information identified from the current observation and subsequent simulation state. |
| next_state_target | object | Target for the change in relative state at the next time step, intended for world model training. |
| relative_distance | number | Euclidean distance between the vehicle and the target docking interface, calculated from their relative positions. |
| contact_risk_score | number | Collision or unintended contact risk score calculated from relative distance, closing speed, attitude error, and control state. |
| docking_phase_index | integer | Ordered integer index representing the search, alignment, approach, contact, and disengagement phases. |
| control_tracking_error | object | Control tracking error calculated by comparing the control action with the actual motion state. |
| relative_bearing_angle | number | Horizontal-plane bearing of the target docking interface relative to the vehicle, calculated from their relative positions. |
| simulation_observation | object | Relative motion, ocean current, and communication states observed by the autonomous underwater vehicle at the current simulation step. |
| communication_quality_score | number | Communication quality score calculated from signal strength, latency, packet loss, and link availability. |
| current_compensated_velocity | object | Relative linear and angular velocity of the vehicle after accounting for ocean current disturbances. |
Compliance Statement
| Authorization Type | Proprietary - Commercial AI Training License (No Redistribution) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- What does the dataset contain?
- It records simulated observations, control actions, relative motion, and communication states as a vehicle approaches a support vessel or underwater station. It also includes docking phases, state transitions, next-state targets, control tracking errors, and contact risk scores.
- Which docking phases and tasks are covered?
- The scenarios cover search, alignment, approach, contact, and disengagement. They can support world model training, state transition and next-state prediction, control tracking analysis, and assessment of unintended contact risk.
- What are the dataset scale and simulation specifications?
- The field definitions cover values such as relative distance, bearing, closing speed, current-compensated velocity, communication quality, and phase index. The record count, sampling frequency, simulator configuration, and value ranges should be confirmed in the product details or delivery documentation.
- How can I obtain the data, and where can I check the license?
- Obtain the dataset through the product page or the platform's stated delivery channel, and check the file format and delivery scope before purchase or download. Commercial use, redistribution, and other permissions are governed by the license terms listed for the product.
Can't find the data you need?
Post a request and let data providers reach out to you.
Get this Dataset
Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Autonomous Underwater Vehicle Docking State Transition Simulation Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/da20b2409e718e825633ddf3ffc97428?dataset_task_cate_id=11},
urldate={2026-10-28},
keywords={autonomous underwater vehicle dataset,underwater docking simulation,underwater robot world model,state transition prediction,underwater control data,docking phase recognition,ocean current simulation,contact risk assessment},
version={1.0}
}Using this in research? Please cite us.
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder