Solution :
-
Data-driven : Deep Learning
-
Support for CCTV, industrial and depth cameras
-
Edge system for sub-second decision making
-
Easy integration with PLCs, Robo-controllers, MES and cloud API
-
Build on industry-leading Nvidia and Microsoft frameworks
-
Quick deployment - speeding up proof of concept and development.
Our Inspiration
-
Highly diverse data: Computer vision deals with an immense variety of data, which necessitates adaptable, data-driven models that can learn from this rich complexity.
-
Expert dependence: Traditional knowledge-driven models rely heavily on experts, limiting their capabilities by the extent of their knowledge and data exposure.
-
Deployment roadblocks: Implementing these models often faces delays due to the intricate interplay of software development, hardware integration, and fine-tuning, demanding expertise across multiple domains.
-
Cloud constraints: The sheer size of computer vision data can pose challenges for cloud deployment, owing to limitations in latency and bandwidth.
Key Challenges in Implementing AI/ML in Manufacturing:
-
Talent Shortage: Difficulty finding qualified professionals with expertise in AI and Machine Learning (AI/ML) specifically relevant to the manufacturing domain.
-
Data & Technology Hurdles: Lack of clear guidance on data collection methods, data-to-AI model interfacing, and selection of appropriate technologies for specific manufacturing needs.
-
Slow Deployment: Delays in implementing AI/ML solutions, often taking months due to complex processes and integration challenges.
-
Real-Time Limitations: Inability to implement real-time inference systems critical for sub-second decision making required in many manufacturing scenarios.
Unlocking Infinite Possibilities with PALMBOTS
INDUSTRIAL INSPECTION
Object Detection
Anomaly
Classification
Code Reading
VIDEO ANALYTICS
Activity Detection
Human Gear detection
Video Anomaly Detection
ROBOTIC PERCEPTION
Robotic Vision Inspection
Robotic Pick and Place
Robotic Human Collaboration