I asked this question on AI stack exchange but didn't get a response.

Basically I'm interested in how you deal with inherent error between your ideal discrete state and your actual state in control planning.

For example, suppose we have a map of an area which is split up into square blocks which represents the possible states of the robot. You then make a plan based upon its starting state - but the real state is somewhat offset from this ideal state.

How do you handle it? If you do a MPC and forward simulate the dynamics, error is going to accumulate - do you replan after every movement? How does it work?


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.