Extended Tactile Perception
We show that robots can extend their perception through grasped tools/objects via dynamic tactile sensing.
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Embedding Symbolic Temporal Knowledge into Deep Sequential Models
We embed symbolic knowledge expressed as linear temporal logic (LTL) and use these embeddings to guide the training of deep sequential models.
Harold wins Annual University and Faculty Teaching Awards!
Harold was awarded the university level and faculty teaching awards for the year 20/21!
Learning Robust Latent Representation for Reinforcement Learning with Multi-Modal Observations
We construct a shared latent space from different sensory modalities via contrastive learning.
Enhancing Deep Learning with Symbolic Knowledge
Bridging the gap between symbolic and connectionist paradigms via Graph Neural Network embeddings
Event-Driven Visual-Tactile Sensing and Learning
Accurate, Fast, and Low-powered Multi-Sensory Perception via Neuromorphic Sensing and Learning