Coding Agents for Generalized Task and Motion Planning Problems
How AI learns to write robot plans that work on new problems
AI systems can write programs that solve robot planning problems better than hand-coded solutions, and these programs work on new situations the AI never saw before. Three different AI models generated programs that succeeded 56% to 95% of the time across 28 different robotic tasks, beating both traditional planners and previous AI approaches.
Building robots that can handle different tasks usually requires experts to manually design planning systems from scratch. If AI can automatically write these programs instead, it cuts the engineering work needed and makes robots faster at solving new problems—the agents used 10 times less computation per task. This could shrink the time between designing a robot task and getting it working in the real world.