Over the past several months, NCRN students Aldo Abou Chedid, Kieran Ratcliffe and Hunter Song, under the supervision of NCRN co-PI Inna Sharf have worked on integrating a depth camera into the end-effector (‘head’) of a feller buncher---a machine operated to cut and grab trees, and to pile them into bunches. The purpose of the camera is to provide operator assistance in planning and sequencing the cutting tasks, as well as to help with localization of the end-effector relative to the trees. This work is a sub-project of Sharf’s research program with NCRN partner FPInnovations, and it led to a new collaboration with the Centre de Formation Professionnelle de Mont-Laurier (CFPML).

After a number of iterations, the design and fabrication of the device housing the camera were completed with the assistance of FPInnovations for manufacturing and CFPML for installation and integration into the feller-buncher crane. Several field tests took place at CPFML over the summer with the device, initially in a controlled environment and then in the forest, during real cutting operations of the feller buncher.

Earlier this fall, Sharf’s team showcased the device with FPInnovations and members of CPFML as part of the shooting for La Semaine Verte-- a Radio-Canada show. Sharf’s group is now teaming up with Scaffold AI (start-up co-founded by Jimmy Li, former NCFRN/NCRN member) to further develop the prototype in combination with a second cabin-mounted camera, as well as a user-interface for assistive information to the operator. 

NCRN P.I and Professor at McGill University Inna Sharf comments: "The long-horizon goals of this research are to increase the autonomy of timber-harvesting machines, to reduce the operator workload and to improve efficiency and safety of these operations"