Fuel your robotic advancements with precise data labeling for robotics industry from our experts. Quality annotations for smarter, more capable machines.
contact usRobotics, being a multifaceted domain, necessitates a wide array of tasks for its development and advancement. Our adept team provides comprehensive and versatile data annotation for robotics industry that cater to the intricate needs of this niche, contributing to the advancement of robotics technology.
Label Your Data addresses the unique challenges posed by different robotic applications, ensuring that each project receives the attention and precision it requires. Whether the goal is to train a robotic hand to delicately pick up small objects or to select ripe fruits, our annotators have the necessary skill set to handle projects ranging from basic to highly complex. Our clients truly benefit from the variety of services we offer and our readiness to tackle any task you need.
We recognize that the heart of every advanced robotics system lies in its ability to perceive and understand the world around it. Computer vision is a cornerstone of the majority of modern use cases in robotics for enhanced visual intelligence of technology. NLP-based data annotation for robotics industry equips robots with the linguistic prowess required to understand, generate, and respond to human language.
By pinpointing objects with precision, we enable your robots to identify and interact with items in their environment.
We segment images into meaningful regions, enhancing your robot’s ability to understand its surroundings in intricate detail.
By performing image classification and categorization, we enable quick decision-making and improved interaction capabilities of the robotic systems.
We annotate key points on objects or subjects for advanced pose estimation, enabling your robots to replicate human-like movements and gestures.
Our annotators identify and classify entities mentioned in text, enhancing your robot’s ability to comprehend context and intent.
By detecting emotions and opinions expressed in text through sentiment analysis, your robots are able to respond empathetically and adapt their interactions.
We categorize text data into relevant classes, teaching your robots to make context-aware decisions.
By pinpointing objects with precision, we enable your robots to identify and interact with items in their environment.
We segment images into meaningful regions, enhancing your robot’s ability to understand its surroundings in intricate detail.
By performing image classification and categorization, we enable quick decision-making and improved interaction capabilities of the robotic systems.
We annotate key points on objects or subjects for advanced pose estimation, enabling your robots to replicate human-like movements and gestures.
Our annotators identify and classify entities mentioned in text, enhancing your robot’s ability to comprehend context and intent.
By detecting emotions and opinions expressed in text through sentiment analysis, your robots are able to respond empathetically and adapt their interactions.
We categorize text data into relevant classes, teaching your robots to make context-aware decisions.
Our key strength is quality. In robotics data annotation, pixel-perfect accuracy is vital for precise robotic movements, which we guarantee for top-tier results.
Our data annotation service for robotics is highly scalable. Starting small, we can swiftly expand annotation tasks using our global team, ensuring on-time project delivery aligned with your deadlines.
Clients often begin with a small MVP project and expand. Label Your Data provides flexible business models, catering to projects of any size, showcasing our adaptability in scope.
Our company holds certifications for PCI DSS (level 1) and ISO:27001, and we adhere to the regulations outlined by GDPR, CCPA, and HIPAA. With 10+ years of experience and 500+ specialists on board, we provide customized data annotation services in robotics for enterprise and R&D projects in 55 languages.
A US-based startup specializing in the development of railway-driving robots with defect identification capabilities sought assistance from Label Your Data. Our collaboration centered around an on-demand model, utilizing small labeling datasets that the client had collected over the course of a year. Precision was of utmost importance, as accurately delineating pixel-perfect polygons was crucial for detecting imperfections such as cracks in the images.
We partnered with a Japanese outdoor robotics company to provide comprehensive image annotation services. Using semantic segmentation, we meticulously labeled diverse outdoor imagery. The project required achieving pixel-perfect accuracy in identifying and categorizing various elements such as mud roads, grassy areas, trees, and road obstacles. This was a short-term endeavor, encompassing the annotation of 20,000 images.
We are currently engaged in an ongoing, on-demand project with an Israeli company specializing in advanced robotics guidance systems. Our collaboration involves annotating small datasets, which are subsequently used to train the robots for specific applications tailored to our client’s customers. To facilitate the process, we are working with the client’s proprietary tooling, for seamless integration of completed annotations into the training workflow.
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More about supervised fine-tuningData is used in robotics to refine algorithms used to train robots and improve the performance of robotic systems through sensor inputs, machine learning, and real-time processing. More specifically, data labeling for robotics industry helps make robots intelligent and competent in AI.
Robotics businesses are countering competitive pressures and technological progress by intensifying R&D efforts for novel solutions, fostering strategic partnerships with tech providers, investing in upskilling their workforce, and implementing flexible business models.
When choosing a robotics data annotation service, important factors include:
Expertise in robotics domain;
Quality control processes;
Scalability for large datasets;
Annotator training and consistency;
Data security measures.
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