Concordia University's Aerospace Robotics Lab

Concordia University's Aerospace Robotics Lab

Concordia University

Dr. Krzysztof Skonieczny

Concordia University’s Aerospace Robotics Laboratory (CUARL) is led by Dr. Krzysztof (Chris) Skonieczny, a professor at the Concordia Institute of Aerospace Design & Innovation (CIADI). His research interests include space robotics, planetary rovers, robot mobility, robot autonomy, vehicle-terrain interactions, advanced 3D printing techniques, robotics excavation & construction, reduced gravity experimentation, computer vision and machine learning for robotics applications. The Aerospace Robotics Laboratory currently supports projects which study and develops robotics for space, especially for applications where a robot interacts with granular terrains in low-gravity environments. Examples include roving on Mars, digging and constructing on the Moon, or sampling and anchoring on comets and asteroids.

Picture galleries

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Example Gallery
An example of gallery using the in-built project page.
FAST NRC 2023 Flights tests
A gallery of pictures of our low-gravity flight field test in May 2023.
FAST NRC 2023 Flights tests
A gallery of pictures of our low-gravity flight field test in May 2023.

Recent Posts

Recent Publications

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See also Dr. Skonieczny’s Google Scholar page.
(2023). Expansion and experimental evaluation of scaling relations for the prediction of wheel performance in reduced gravity. Microgravity Science and Technology.

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(2023). Systematic solution for optimally energy-efficient turning radius for wheeled skid-steer rovers. Robotics and Autonomous Systems.

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(2022). An Equivalent Time-Optimal Problem to find Energy-Optimal Paths for Skid-Steer Rovers.

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(2022). Power and energy consumption of skid-steer rovers turning on loose soil. Journal of Field Robotics.

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(2022). Three-dimensionsal granular flow continuum modeling via material point method with hyperelastic nonlocal granular fluidity. Computer Methods in Applied Mechanics and Engineering.

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(2022). Gravity sensitivity of continuum numerical solvers for granular flow modeling. Granular Matter.

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(2022). Comparison of wheel load application methods in single-wheel testbeds. Journal of Terramechanics.

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(2022). Experimental evaluation of cone index gradient as a metric for the prediction of wheel performance in reduced gravity. Journal of Terramechanics.

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(2021). Lunar analogue dataset for traversability assessment and novelty detection.

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Recent & Upcoming Talks

Past and present team members

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Contact

Contact us with any questions about our research or to join our team