This project is about studying and developing demonstrably practical methods and algorithms for reconnaissance activities using multiple robotic vehicles, with a particular focus on especially harsh and uncertain terrains (e.g., rocky, forested, unstructured, off-road) as well as on the problem of maintaining secrecy from potential intruders in such operations. The proposed research includes work on vehicle navigation, robot teaming, learning-based control, terrain assessment, as well as the concepts of opacity and unobservability for maintaining secrecy, where some vehicles may be only semi-autonomous, remotely driven, and/or supervised by human operators. In addition to this fundamental research, the project plan includes integration on actual mobile robots and field testing in representative environments. Although reconnaissance is the primary interest of the research partners associated with this project, it is anticipated that this research may also find application in other Canadian “off-road” scenarios, including mining automation, forestry, agriculture, as well is in planetary exploration and science. The proposed project also aims to provide unique HQP training experiences on multiple fronts. Student researchers will be given the opportunity to not only collaborate across several disciplines, but also take theory into practice by way of access to state-of-the-art mobile robots and field testing environments.
Joshua Marshall (PI), Sidney Givigi, Karen Rudie, Brian Surgenor
NSERC Collaborative R&D Program
General Dynamics Land Systems Canada (GDLS-C)
Defence R&D Canada (DRDC) Suffield