From Collaborative Robot to Collaborative Space: Intelligent Human-Robot Collaboration for Smart Factory

To enable safe and effective human-robot collaboration (HRC) in smart manufacturing,seamless integration of sensing, cognition and prediction into the robot controller is criticalfor real-time awareness, response and communication. Further complicating matters, therobot is co-operating within a heterogeneous manufacturing environment (robots, humans,equipment). Therefore, the specific research objective of this thesis is to provide the robotProactive Adaptive Collaboration Intelligence (PACI) and switching logic within its controlarchitecture. That is, give the robot the ability to optimally and dynamically adapt itsmotions given a priori knowledge and predefined execution plans for its assigned tasks,and detected human actions. The challenge lies in augmenting the robot's decision-makingprocess to have a greater situation awareness and to yield robot behaviors/reactions subjectto different human-robot actions while simultaneously maintaining safety and productionefficiency.The work was carried out using ROS Melodic Morenia (running on Ubuntu 18.04Bionic Beaver) since it is today's standard platform for robotic research and ensures greatscalability and maintainability of the system. Inside this framework, a control architecturewas developed to have features:flexibility(suitable for a large range of applications),accessibility(user friendly interface),modularity(selective and expandable path planningtechniques, high-level controllers, behavior definitions),safetyandproductivity. Robotreactive behaviors were achieved via cost function-based switching logic activating the bestsuited high-level controller. The cost is a function of safety (e.g., obstacle/human proximity)and productivity (e.g., induced time delays). Leveraging the availability of numerous pathplanning and robot controllers in existing open-source robot libraries (MoveIt!), the PACI'sunderlying segmentation and switching logic framework was demonstrated to yield a highdegree of modularity and flexibility. Using a hardware-in-the-loop testbed setup, theperformance of the developed control architecture subjected to different levels of human-robot interactions was validated in the University of Florida e.DO robot testbed, simulatingperception of the human operator.This research has been carried out at University of Florida (Gainesville, FL, USA),member of a multi-university/industry international collaboration. It represents the startingpoint for a long-term project funded by NSF-NRI and called "Intelligent Human-RobotCollaboration for Smart Factory".