In-the-Wild Data Collection
Grippers and Sensor Integration
Collect real-world data from diverse environments using robotic grippers equipped with advanced sensors like cameras, LiDAR, and force sensors. Capture data in various settings—warehouses, factories, and outdoor environments—to train AI models for tasks such as object manipulation, navigation, and interactions with unstructured surroundings.
Controlled Environment Data Collection
Lab-Based Controlled Settings
Gather data in controlled laboratory environments using robotic testbeds where variables like lighting, materials, and obstacles can be precisely adjusted. This approach is ideal for producing consistent datasets for tasks such as precision assembly and quality control in industrial robotics.
Crowdsourced Data Collection
Crowdsourced Validation
Leverage human-in-the-loop approaches with crowdsourced data annotation, allowing human reviewers to validate or correct robotic actions and sensor data interpretations. This iterative feedback process continuously refines and improves AI models for robotic systems.
Virtual Reality (VR) Simulated Data Collection
Train in Simulated Environments
Simulate complex scenarios in virtual reality (VR) environments to safely gather data without real-world risks. Train robotic AI models in object recognition, navigation, and human-robot interaction, and test edge cases that are challenging to recreate in real life.
Multi-Sensor Fusion
Combine 2D and 3D Data
Integrate data from multiple sensors, including cameras, LiDAR, ultrasonic sensors, and radar, to create rich datasets. This fusion of 2D and 3D sensor data enhances robotic perception for tasks like navigation, obstacle avoidance, and environmental understanding.
Maximize Your Impact with Precision
Use Cases
Autonomous Navigation
Train AI for self-driving robots in industries like logistics, agriculture, and manufacturing.
Industrial Automation
Develop AI systems for automated assembly lines, enhancing efficiency and reducing errors in production.
Robotic Surgery
Annotate precise movement data for medical robots, improving accuracy in surgical procedures.
Warehouse Automation
Enhance AI models for autonomous robots handling inventory, optimizing speed and accuracy in logistics.
Home Robotics
Enable household robots to perform tasks like cleaning, security, and assistance with high accuracy.
Drones and UAVs
Develop AI for autonomous aerial vehicles to perform tasks like mapping, delivery, and surveillance.
Rescue and Disaster Response
Train robots for search and rescue operations, ensuring they can navigate complex and hazardous environments.
Human-Robot Interaction
Build AI models that allow robots to interact smoothly with humans in various settings, from customer service to healthcare.
