Inspired by Social Projection Theory, we use the robot's self model to efficiently model humans.
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We propose a deep switching state space model that can capture both state-dependent and time-dependent switching patterns in time series data.
Abdul Fatir Ansari successfully defended his thesis and is now Dr. Ansari. Congratulations Fatir!
Sreejith Balakrishnan is awarded the Research Achievement Award for his NeurIPS 2020 paper on efficiently exploring reward functions in Inverse Reinforcement...
We have won the Best Paper Award at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2021 in October. IROS is a premier flagshi...
We show that robots can extend their perception through grasped tools/objects via dynamic tactile sensing.
We embed symbolic knowledge expressed as linear temporal logic (LTL) and use these embeddings to guide the training of deep sequential models.