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Cognitive Navigation and Task Reasoning in Field Robotics
This project explores how a mobile field robot integrates semantic perception, task reasoning, and task-aware planning to operate autonomously in unstructured, real-world environments. The work focuses on implementing and evaluating existing perception and task-reasoning components that enable the robot to interpret visual and spatial information, infer task intent, and select feasible actions under uncertainty. Experiments are conducted primarily on the ANYmal quadruped robot, with Unitree Go1/A1 platforms used for rapid prototyping and early validation. The project progresses from simulation to field testing over a four-month period, assessing task execution performance and the quality of semantic environment mapping. Conducted in collaboration with the UCL Robot Perception and Learning Lab, the project supports supervised undergraduate research training and strengthens international research ties by providing access to advanced robotic platforms and academic expertise in AI-enabled robotics.
Faculty Supervisor:
Inna Sharf
Student:
Partner:
University College London
Discipline:
Engineering
Sector:
Education
University:
McGill University
Program:
Globalink Research Award
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Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.