MOST - Task-relevant perception and control for human-oriented operation of mobile manipulators in semi-structured environments

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The rise of e-commerce has made logistics (material handling) the fastest-growing industry today with the annual growth rate of 10-15% worldwide. The digitalization of consumer markets is also calling for new paradigm of manufacturing to cope with increasing demands for short-life cycle products and burst manufacturing. The immediate consequence of this trend is the urgent need for a faster and more efficient operation of large scale material handling plants such as sorting facilities for parcels, distribution centers for digital retail and machine tool factories for discrete-part manufacture. These indoor areas are "semi-structured" in the sense that fixed installations (shelves, workstations) are blended with dynamic unpredictable entities (human workers, indoor vehicles) to transfer numerous objects in different sizes, shapes and properties. This research brings together experts in control, sensing, HRI (Human-Robot Interaction) and machine intelligence from Canada and Taiwan to develop intelligent mobile manipulators that can operate side-by-side with humans in semi-structured environments. In order for robots to collaborate with humans in an intuitive and reliable manner, we emphasize the formal methods for HRI and shared autonomy. New sensing and decision making algorithms will be developed to allow robots to navigate through dynamic environments safely and manipulate objects with human-like dexterity. This research builds on existing infrastructure including the mobile manipulator testbeds in both research groups as well as the new RoboHub facility at Waterloo, a high-tech indoor space for robot testing and validation. The demand for more labor is increasing in logistics and material handling, yet the available workforce will decrease due to shrinking population and aging. This research will lay the foundation for next generation of material handling facilities where mobile manipulators can coexist and operate seamlessly with human workers. The new knowledge and techniques from this research will also foster progresses in other areas including perception, autonomous navigation, biomechatronics, personal and healthcare robotics. This project is submitted under the international agreement between NSERC and MOST.