Siyu Li

A reinforcement learning (RL) approach to automatically generate the multimodal policy of the robot and offers a scalable and interpretable alternative for designing interaction managers in multimodal human-robot collaborations.

Angular-to-Cartesian projection distortions have long bottlenecked spherical 3D perception, but explicitly modulating voxel features with spherical range-azimuth geometry outperforms top surround-view models like SurroundOcc and TPVFormer across varied wild environments.

Escalating to a larger LLM is counterproductive when it corrupts correct answers, meaning optimal cascading requires routing on net rescue-versus-harm rather than model uncertainty.