Robotics
Deep Learning in the Robotics Industry
Why Embedl is Important for the ROBOTICS Industry
The robotics industry is evolving at an unprecedented rate, with AI and machine learning playing a crucial role in enhancing automation. However, one of the biggest challenges in robotics is optimizing AI models to perform efficiently on edge devices with limited computational power while maintaining high production quality and reliable performance.
This is where Embedls Model Optimization SDK steps in. It helps optimize machine learning models, making them faster, lighter, and more efficient, ensuring stable, precise, and high-quality AI-driven robotics that perform consistently across various industries.
Embedls SDK
Faster AI Inference
Optimized AI models run with lower latency, enabling real-time decision-making for robots.
Cost Reduction in Hardware Requirements
Robotics companies can use cost-effective processors instead of expensive GPUs, lowering production costs.
Energy Efficiency and Battery Optimization
Reduced computational load translates to lower energy consumption, extending battery life in mobile robots.
Enhanced Precision and Reliability
Optimized AI models improve accuracy and consistency, reducing errors in robotic decision-making and ensuring high production quality.
Increased Production Quality
Embedls SDK optimizes AI models for superior accuracy, consistency, and efficiency, ensuring stable and reliable performance across diverse real-world conditions, ultimately enhancing overall production quality.
Scalability and Adaptability
Embedls SDK seamlessly integrates with multiple AI frameworks and hardware platforms, enabling effortless deployment across diverse robotics applications while ensuring flexibility for future advancements.
case study
Semantic Segmentation in real-time on TI’s TDA4VM
In this case study, we will focus on the Lightweight Atrous Spatial Pyramid Pooling (LRASPP) model, an architecture specifically designed for efficient semantic segmentation on mobile and embedded platforms.
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