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Robotics

Annotate 3D models and LIDAR points to assist robots in preventing crashes through object detection

Industry and use case:

Robotics, autonomous navigation

Data:

10,000 street images

Project duration:

1,5 months
Robotics

Challenge:

The goal was to train the autonomous robot to navigate real-world environments. The client wanted to annotate 10 thousand images obtained from the robot’s RBG camera to train the neural network. The quality of data labelling was paramount because the robot was going to navigate the streets of a metropolitan centre, and the cost of navigation error was high. It led to a large number of annotation classes

Solution:

The Training Data team consisted of 70 people and was split into 5 groups, including a separate quality assurance unit. Each group was responsible for specific annotation classes and verifying other teams’ work. Teams organization in this structure allowed us to eliminate human annotation errors within our processes

Outcomes:

The customer trained a neural network and conducted field tests that demonstrated that the robot could select the perfect route to overcome obstacles:

  • 99% annotation quality
  • The customer saved a lot of time delegating quality assurance to our team
Our goal was to pass the autonomous robot tests successfully. Thanks to the cohesive and independent work of the Training Data teams, we trained the robot on an excellent dataset and passed field trial.
Ivan N.
Project Manager

Stages of work

  • Application

    /01
    Leave a request on the website for a free consultation with an expert. Th e acco unt manager will guide you on the services, timelines, and price
  • Free pilot

    /02
    We will conduct a test pilot project for you and provide a golden set, based on which we will determine the final technical requirements and approve project metrics
  • Agreement

    /03
    We prepare a contract and all necessary documentation upon the request of your accountants and lawyers
  • Workflow customization

    /04
    We form a pool of suitable tools and assign an experienced manager who will be in touch with you regarding all project details
  • Quality control

    /05
    Data uploads for verification are done iteratively, allowing your team to review and approve collected/annotated data
  • Post-payment

    /06
    You pay for the work after receiving the data in agreed quality and quantity

Timeline

  • 24 hours
    Application
  • 24 hours
    Consultation
  • 1 to 3 days
    Pilot
  • 1 to 5 days
    Conducting a pilot
  • 1 day to several years
    Carrying out work on the project
  • 1 to 5 days
    Quality control
You pay for the work after you have received the data
in the established quality and quantity

Why
Training Data

  • Quality Assurance:
  • Enhanced Data Accuracy
  • Consistency in Labels
  • Reliable Ground Truth
  • Mitigation of Annotation Biases
  • Cost and Time Efficiency
  • Data Security and Confidentiality:
  • GDPR Compliance
  • Non-disclosure agreement
  • Data Encryption
  • Multiple data storage options
  • Access Controls and Authentication
  • Expert Team:
  • 6 years in industry
  • 35 top project managers
  • 40+ languages
  • 100+ countries
  • 250k+ assessors
  • Flexible and Scalable Solutions:
  • 24/7 availability of customer service
  • 100% post payment
  • $550 minimum check
  • Variable Workload
  • Customized Solutions
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