Enhancing Pick-and-Place Robots with Annotations from Scale Rapid

• Analytics & Modeling - Machine Learning
• Sensors - GPS

• Cement
• E-Commerce

• Maintenance
• Quality Assurance

• Autonomous Robots
• Construction Management

• System Integration
• Training

Ambi Robotics provides AI-powered robotic systems to customers, enabling them to scale their operations and handle increasing supply chain demand. The company's machine learning (ML) system is responsible for identifying an object and its location, and moving the robot hand to that location to grasp the object. The pick success rate, which is how often a robot successfully picks up an object, is the most important marker of success. However, Ambi Robotics faced a challenge in obtaining high-quality annotations for their data, which is crucial for improving their models. Initially, the company was managing the annotation process in-house, but this approach was not scalable for the amount of data they needed. When working with new clients and locations, Ambi Robotics would sometimes see lower pick-and-place success rates, simply because the environment looked different. The best way to improve performance was to mine data from the new location, annotate it, and then retrain their ML model. However, the company lacked the infrastructure to process this large quantity of data on a recurring basis.

Ambi Robotics is a company that provides customers with AI-powered robotic systems that empower them to scale their operations and handle increasing supply chain demand. Their technology is used in logistical warehouses across the e-commerce industry to automate the process of picking up packages, scanning their barcodes, and sending them to the correct location. The company's machine learning (ML) system is responsible for not just identifying an object and its location, but also for moving the robot hand to that location to grasp the object. For these customers, pick success rate – how often a robot successfully picks up an object – is the most important marker of success.

Ambi Robotics partnered with Scale Rapid to outsource the data annotation process, enabling them to quickly obtain the annotations they needed to improve their ML models. Scale Rapid offers a simple step-by-step approach for setting up the annotation process, making it easy for customers to set up a new task in just minutes. To provide high-quality data, Scale Rapid builds quality evaluation into their pipeline through batch annotation. They produce a calibration dataset to identify gaps in the labeling instructions, until the customer is satisfied with the data calibration. After calibration is complete, Scale Rapid produces a production batch for the client. Scale Rapid has also provided Ambi Robotics with a reduction in lead time. While Ambi Robotics’ internal annotation process could sometimes take weeks, Scale Rapid consistently delivers production-ready results within 1-2 days. The results delivered by Scale Rapid are consistently on-level with their in-house annotation, while being produced using robust and scalable infrastructure.

• With the help of Scale Rapid, Ambi Robotics has been able to improve the pick-and-place performance of their robotic systems, making them more robust to new clients and locations. When the company sees degraded model performance at a new customer location, they can now simply mine the relevant data and send it to Scale for annotation. Then, they can retrain their ML models using these data annotations. This has made the model improvement process much easier. After incorporating Scale Rapid into their production pipeline, Ambi Robotics can obtain high-quality data annotations quickly and easily, making it simple to use continuous learning to improve their system’s pick success rate.

• Scale Rapid consistently delivers production-ready results within 1-2 days, compared to Ambi Robotics’ internal annotation process which could sometimes take weeks.
• Scale Rapid's results are consistently on-level with Ambi Robotics' in-house annotation.
• Scale Rapid's process allows Ambi Robotics to set up a new task in just minutes.