Leveraging LLMs to integrate autonomy into Robots

At Polymath, we try to find bottlenecks in our engineering process and find creative ways to solve them. In general we are skeptical of AI solutions. We have heard of solutions that claim to "build a robot." But building robots is not as easy as some of the AI hype claims. The real question for us is, "what areas can AI be helpful to robotics?"

Polymath is a company that makes off-highway vehicles autonomous. Our goal is to find the best tools to help our clients get their vehicles to autonomously do the tasks they want their vehicles to do. 

At Polymath, we try to find bottlenecks in our engineering process and find creative ways to solve them. In general we are skeptical of AI solutions. We have heard of solutions that claim to "build a robot." But building robots is not as easy as some of the AI hype claims. The real question for us is, "what areas can AI be helpful to robotics?"

 Recently we found a way that AI, specifically RAG based LLMs, could be helpful. A bottleneck our engineers faced was creating DBC files. You can think of DBC files as the Rosetta Stone between the robot and our software. We call our software the Hardware Abstraction Layer (HAL). 

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