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Can we teach a robot its limits to do chores safely & correctly? 🧵 To help robots execute open-ended, multi-step tasks, MIT CSAIL researchers used vision models to see what’s near the machine & model its constraints. An LLM sketches up a plan that’s checked in a simulator to... show more
28,315 Aufrufe • vor 1 Jahr •via X (Twitter)
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Their trial-&-error method is called "Planning for Robots via Code for Continuous Constraint Satisfaction" (PRoC3S). It tests long-horizon plans to ensure they satisfy all constraints & enables a robot to perform diverse tasks, like writing individual letters, drawing a star, & sorting & placing blocks in different positions.

The researchers’ method uses an LLM pre-trained on text from across the Internet. Before asking PRoC3S to do a task, the team provided their language model w/a sample task (like drawing a square) that’s related to the target one (drawing a star). The sample task includes a description of the activity, a long-horizon plan, & relevant details about the robot’s environment.

In simulations, PRoC3S successfully drew stars & letters 8/10 times each. It also could stack digital blocks in pyramids & lines, & place items w/accuracy, like fruits on a plate. Across each of these digital demos, the CSAIL method completed the requested task more consistently than comparable approaches like "Code as Policies."

Next, the CSAIL engineers brought their approach to the real world. Their method developed & executed plans on a robotic arm, teaching it to put blocks in straight lines. PRoC3S also enabled the machine to place blue & red blocks into matching bowls & move all objects near the center of a table.

In the future, PRoC3S could help robots complete more intricate chores in dynamic environments like houses, where they may be prompted to do a general chore composed of many steps (like "make me breakfast").

For future work, the researchers aim to improve results using a more advanced physics simulator, & to expand to more elaborate longer-horizon tasks via more scalable data-search techniques. They also plan to apply PRoC3S to mobile robots (such as quadrupeds) for tasks that include walking & scanning surroundings.

Authors: Aidan Curtis (@AidanCurtis3), Nishanth Kumar (@nishanthkumar23), Jing Cao, Tomás Lozano-Pérez, & Leslie Pack Kaelbling (@MIT_LISLab) Website: Full video:

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ew! no, no you can’t. you can do other things, but, no - the word ‘teach’ doesn’t actually apply in this context. its usage is an annoying misuse of language that shouldn’t be coming out an academic institution of your standing. Pedagogy has a long history. who’s your audience?

I understood exactly none of that

C'est vraiment intéressant! Les applications potentielles pour l'apprentissage automatique et la robotique sont énormes
