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MISCO is developed, a novel evolutionary framework empowered by deep generative models to optimize VSR designs with theoretical guarantees that represents a step change towards more scalable and reliable soft robot development.
This work presents RoboLDA, a Bayesian probabilistic model that decomposes VSR morphology generation into a four-level hierarchy:"task-robot-organ-voxel", and is trained via variational inference, which pioneers hierarchical generative modeling of robot morphology.
CoNav-UAV is proposed, which explicitly models the target-oriented vision-and-language navigation task as a Stackelberg game between a high-altitude leader and a low-altitude follower, with the system operating on onboard visual and linguistic inputs alone.
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