In fact, we can’t answer that question. But sometimes we don’t need to define it clearly. The human learning process is so wonderful that we can classify them accurately under a general concept.
Robots, are not people who work as machines , nor merely machines who look alike humans being. From the perspective of human beings, as long as it can replace one or several kinds of human labor, it can be called robot, such as chat robot and automatic trading robot.
Those robots are not in the category we are talking about today. What we are talking about is a small category of robots, which have hardware entities and can move, such as automated mobile robot, mechanical arm, UAV and so on (as shown in the figure below).
There are three categories:
1 Autonomous Movement: sensor fusion, localization, mapping, navigation
2 Human-Computer Interaction: task planning, NLU, intention detection, imitation learning,
3 Intelligent control：collection detection, motion planning, reinforcement learning, 3D scene understanding
At present, the production application has penetrated into all aspects of production. Within the established procedures and scope, it has realized the functions of processing, taking and placing, carrying, and so on.
However, it is not necessary to invest robots in all production links. Before putting into an application, a comprehensive technical and economic benefit evaluation should be conducted to ensure that their production and application meet the following requirements:
① It should meet the requirements of the production process and integrated equipment.
② Meet the requirements of production load and safety protection.
③ The action time should meet the requirements of production rhythm and production efficiency.
④ Robot grasping materials should meet the quality requirements of accuracy and standard.
Common Labeling Tools in Robotics
2D Bounding Boxes, 3D Bounding Boxes, Semantic Segmentation, Video Tracking
Common Labeling Types:
- Object Recognition
- Object Tracking in Video
- Semantic Segmentation
Data, Algorithms, and Processing are Three indispensable Elements of AI.
Data is the starting point.
It makes sense for AI to start with data and take advantage of learning itself. In scalable data and the high-speed era, it is very convenient to use data to train artificial intelligence.
The original data is generally acquired through data collection, and the subsequent data cleaning and data annotation are equivalent to processing the data, and then transferred to the artificial intelligence algorithm and model for invocation.
If the data used in artificial intelligence training is not sufficiently diverse and unbiased, problems such as artificial “AI bias” may arise.
Aware of those challenges, ByteBridge moves a big step forward through its automated data collection and labeling platform. It provides high-quality training data for the machine learning industry.
- ML-assisted capacity can help reduce human errors by automatically pre-labeling
- The real-time QA and QC are integrated into the labeling workflow as the consensus mechanism is introduced to ensure accuracy
- Consensus — Assign the same task to several workers, and the correct answer is the one that comes back from the majority output
- All results are thoroughly assessed and verified by a human workforce and machine
In this way, ByteBridge can affirm our data acceptance and accuracy rate is over 98%.
In addition, we can provide personalized annotation tools and services according to customer requirements.
- Clients can set labeling rules, iterate data features, attributes, and task flows, scale up or down, make changes.
For example, you can choose a Bounding Box and Classification Template on the dashboard:
Clients can monitor the labeling progress and get the results in real-time on the dashboard.
These labeling tools are already available on the dashboard: Image Classification, 2D Boxing, Polygon, Cuboid.
We can provide personalized annotation tools and services according to customer requirements.
A collaboration of the human-work force and AI algorithms ensure a 50% lower price compared to the conventional market.
If you need data labeling and collection services, please have a look at bytebridge.io, the clear pricing is available.
Please feel free to contact us: firstname.lastname@example.org
1 How the Data Annotation Service Empowers Robotics in 2021? — Part2
2 How Data Labeling and Annotation Services Empower Logistics in 2021?
3 Customer Needs and Wants in Data Annotation Services
4 No Bias Training Data — the New Bottlenecks in Machine Learning
5 How Data Annotation Service Accelerates AI Application in the Field of Industry?