  This paper studies real-time collaborative robot (cobot) handling, where the
cobot maneuvers an object under human dynamic gesture commands. Enabling
dynamic gesture commands is useful when the human needs to avoid direct contact
with the robot or the object handled by the robot. However, the key challenge
lies in the heterogeneity in human behaviors and the stochasticity in the
perception of dynamic gestures, which requires the robot handling policy to be
adaptable and robust. To address these challenges, we introduce Conditional
Collaborative Handling Process (CCHP) to encode a contextaware cobot handling
policy and a procedure to learn such policy from human-human collaboration. We
thoroughly evaluate the adaptability and robustness of CCHP and apply our
approach to a real-time cobot assembly task with Kinova Gen3 robot arm. Results
show that our method leads to significantly less human effort and smoother
human-robot collaboration than state-of-the-art rule-based approach even with
first-time users.
