This questionnaire aims to systematically understand the real needs of our clients (including startups and large technology enterprises) regarding dexterous manipulation data, providing a decision-making basis for building a hierarchical dataset library and SaaS service platform to offer better product services to clients with data need.
1. Company Name_______________________________________________ Location Company Type Robotics Startup (Founded Date） Large Tech Company Traditional Manufacturing Transformation Research Institution/University Other
Number of Employees 50 50-200 200-500 500-2000 ＞2000
Current Development Stage Proof of Concept（POC） Product Development Pilot Production Mass Production Market Maturity
6. Please describe specific tasks for your selected scenarios
e.g., camera module installation in 3C assembly, irregular object grasping in warehousing
Scenario 1：____________ Scenario 2：____________
Scenario 3：____________
The most needed dexterous manipulation data types (ranked 1-5 by importance, with 1 being the most important) Multi-modal sensor data (vision + tactile + force feedback) Human demonstration trajectory data Dexterous hand manipulation data Dual-arm coordination data Tool usage data Failure case data Edge case/long-tail data Other
Data Collection Environment Requirements Laboratory standard environment Real industrial environment Home/commercial environment Outdoor/special environment Multi-environment mix
Data Annotation Requirements Raw data only Basic annotation needed (object position, pose, etc.) Fine-grained annotation needed (contact points, force, intent, etc.) Multi-level annotation needed Other requirements:
Data Reusability/Migration Requirements: Are there any of the following situations?
The same task requires repeated data collection on different robot bodies/configurations Existing data is difficult to migrate to different robotic arms/end-effectors The model needs to be fine-tuned almost from scratch on the new ontology Data/strategy migration has been attempted, but the results are unstable or uncontrollable There is currently no such requirement
Data Reusability/Migration Status: How reusable is the data under the following circumstances? (1 = Very Difficult, 5 = Very Easy) |
Same task, different robotic arm brands/models Same task, different end-effectors (gripper / dexterous hand / others) Different Degrees of Freedom / Configurations Same strategy, from simulation → reality Same strategy, from human demonstration → robot execution
Data volume per scenario（Trajectories） ＜1000 1K-10K 10K-100K ＞100K
Data update frequency One-time purchase Quarterly updates Monthly updates Continuous subscription
Data Quality Requirements
Data Quality Requirements-Success rate >60% >80% >90% >95%
Data Quality Requirements-Diversity 单一场景 | Single scenario 有限变化 | Limited variations 高度多样化 | Highly diverse
Data Quality Requirements-Data Precision 标准精度 | Standard precision 高精度 | High precision 超高精度 | Ultra-high precision
Special Data Requirements Specific operator data needed (e.g., professional technicians) Specific object/material data needed Specific environmental condition data needed Customized collection needed Other
19. Your Robotic arm brand/mode______________ End-effector type Dexterous hand Gripper Suction cup Other
Data Format and Interface Requirements-Preferred data format HDF5 ROS Bag JSON 自定义格式 | Custom format
API interface requirements RESTful API gRPC SDK Other:
Data preprocessing service needed Yes No
Data preprocessing service needed-Primary algorithm framework PyTorch TensorFlow JAX Other
Pre-trained models needed Yes No
Model fine-tuning service needed Yes No
SaaS Service Expectations-Preference for tiered database services Open-source basic datasets (free/low-cost) Semi-open industry datasets (medium cost) Closed-source high-quality datasets (premium) Customized data collection services Hybrid solution
SaaS Platform Feature Expectations (Multiple Choice) Online data browsing and filtering Data download and management Online data annotation tools Data quality assessment tools Model training environment Data augmentation services Collaboration and version control Other
Data Security and Compliance Requirements Data localization deployment Encrypted data transmission Access control management Compliance certification (ISO/GDPR, etc.) Other
Budget Range (Annual data procurement budget in USD) ＜100K 100K-500K 500K-2M 2M-5M ＞5M
Preferred Payment Model One-time purchase Pay per data volume Subscription (monthly/quarterly/annual) Pay per usage Customized project collaboration
Most valued service factors (Rank 1-6) Data quality Data scale Price Delivery speed Technical support Customization capability
Main pain points in acquiring dexterous manipulation data
Willing to participate in follow-up in-depth interviews Yes (Contact) No