Detect, Reject, Correct: Crossmodal Compensation of Corrupted Sensors
Michelle A. Lee,Matthew Tan,Yuke Zhu,Jeannette Bohg,Michelle A. Lee,Matthew Tan,Yuke Zhu,Jeannette Bohg
Using sensor data from multiple modalities presents an opportunity to encode redundant and complementary features that can be useful when one modality is corrupted or noisy. Humans do this everyday, relying on touch and proprioceptive feedback in visually-challenging environments. However, robots might not always know when their sensors are corrupted, as even broken sensors can return valid values...
