The Sequence Scope: ML, Physics and Robotics

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TheSequence | Ksenia Semenova | Substack

📝 Editorial: ML, Physics and Robotics

Robotics is one of the quintessential use cases for machine learning (ML) but also one of the most difficult ones to implement. Robotic applications need to combine hardware and ML models in very complex ways and are subjected to interactions with real-world environments, which are very hard to model. Object interactions, texture, environmental dynamics, advanced geometry are common elements that need to be present in physic simulation models. Not surprisingly, physics simulation is one of the hardest things to get right in ML solutions. The absence of robust simulators remains one of the biggest obstacles to making robotics research mainstream. Many of the physic simulation stacks remain closed-source and based on proprietary solutions. However, the ML…