I work at SoundHound where we've been worried about these issues. (I'm going to plug our recent work...) Our new approach is to do natural language understanding in real-time instead of at the utterance (turn) taking level. That way we can give the user constant feedback in real-time. In the case of a screen that means the user sees right away that they are understood, and if not, a better hint of what went wrong. For example a likely mistake is an ASR mistranscription for a word or two.
We still need to prove this is a better paradigm for VoiceAI in products that people can try for themselves, and are working towards that goal. I hope that voice interfaces that were clunky with turn-taking will finally be more naturally usable with real-time NLU.
I'm eager to find references on modern approaches to robotic control.The coordinated robots from Boston Dynamics (acquired by Google) impress the most, with their ability to react quickly to perturbation and move competently over difficult terrain.I assume they are not solving inverse kinematics problems continuously, and also assume that much of their progress was made before the deep learning...