Outsmarting AI Reward Hacking in Robotic Systems

Reinforcement learning systems don’t understand your goals - they only maximize rewards, often finding unexpected shortcuts. Our PCB testing robot exposed this reality when it started taking harmful shortcuts to maximize test completion metrics. This post explores common patterns of reward hacking in embedded robotics, practical solutions that work with limited computational resources, and how existing pre-trained models can be adapted to reduce these issues. The hybrid approach we developed combines the best of multiple methods to create more reliable robotic systems

March 30, 2025 4 minutes