Grants and Contributions

The Centre for Surgical Invention and Innovation developed an Image-Guided Automated Robot (IGAR) designed to carry out automated, preplanned, imaging-technology-guided surgical procedures. IGAR's medical procedures have proven to be equivalent in precision, comfort, and time with less pain and better cosmetic outcomes than the standard manual procedure.

This feasibility study proposes to merge IGAR with the IBM Watson Cognitive Computing System, allowing Watson to plan and control the execution of IGAR's surgical tasks. This will be the first demonstration of a fully autonomous medical robotic system in the world. This technology would be vitally important to the future of human space exploration and colonization, as well as improve quality and access to health care on Earth.

Light detection and ranging (lidar) sensors are essential tools used for a variety of tasks such as terrestrial topographic mapping, navigation and docking in space, and landings on planets or asteroids.

Teledyne has proposed to develop a compact array sensor. The improved lidar system will reduce the size and weight of the equipment, while increasing the range, coverage rate, and resolution of mapping technologies.

A light detection and ranging (lidar) 3D imaging sensor uses lasers to produce representations of an environment or object. Lidar is crucial for robotic navigation technologies. A small, low-cost, lighting-immune 3D sensor is highly desired for potential future planetary rover missions.

Neptec is proposing the development of a next-generation miniaturized lidar platform which addresses customer needs and future trends in both terrestrial and space markets. This will be accomplished through the manufacture and testing of two mini lidar prototypes, one focusing on performance and readiness for flight, and the other prioritizing miniaturization over performance. These projects will leverage Neptec's experience and expertise in developing lidar systems for space, using the successful TriDAR as a foundation for the proposed architecture.

With advances in miniaturization of electronics, new materials and new manufacturing methods, significant space missions that were once the exclusive domain of large spacecraft can now be performed using spacecraft that are one-tenth the size. One factor still limits the types of missions that these new small and nimbler spacecraft can perform: the lack of significant propulsion that is safe, affordable and easy to integrate.

Continuum Aerospace, with partners Canadore College and the University of Waterloo, are leveraging expertise in new rocket propulsion technologies, direct metal laser sintering 3D printing, and enhanced computational modelling to develop a new thruster system using non-toxic, easy-to-handle propellants which is small enough to fit these smaller spacecraft designs. This thruster system will be the first of its kind in Canada, and will provide Canadian spacecraft designers and mission planners with the ability to undertake new types of missions at a lower cost with enhanced thrust.

Understanding how physiological signals behave in extreme conditions could lead to monitoring systems that would improve the health and safety of astronauts during future long-duration exploration-class missions. A wearable monitoring system would serve as a constant diagnostic tool that could detect meaningful physiological changes and inform the user.

The objective of this project is to investigate the feasibility of developing a wearable monitoring platform for extreme environments and to collect a physiological data set to form a baseline for a broad array of contexts. The development of such monitoring technologies would not only change how the space domain deals with the health and safety of astronauts, but could also transform sectors on Earth such as medical care, defence and aviation.

Current path planning systems for NASA's Mars rovers require extensive human input that can lead to wasted mission operations, due to communication delays and time-consuming manual analysis of data gathered from orbit and the rover.

The Intelligent Path Planner (IPP) allows for heterogeneous data sets to be aggregated in real time, enabling rovers to learn as they drive. The IPP uses the information it has gathered to influence the path it plans, while also adapting the path based on the terrain encountered. Machine learning teaches the IPP to associate different terrains with performance levels. The IPP is targeted as a software upgrade to improve the efficiency, safety and scientific return of rover missions without the need for specialized sensors.

This project will develop a prototype synthetic cognitive decision support system for medical diagnostics during space flight, and will involve an initial validation of that system.

The proposed Synthetic Intelligence for Medical Assessment and Treatment (SIMAT) will simulate human cognitive diagnosis through the application of decision algorithms, statistical analysis, pattern recognition, and machine learning. Once fully developed, it will assist Crew Medical Officers in analyzing an ailing crewmember's medical symptoms and forming diagnoses. This technology will be critical for future long-duration, exploration-class missions where communication with Earth is delayed due to the vast distances involved. It will also support medical operations when communication with Mission Control is interrupted, or in circumstances where a medically trained astronaut is unavailable or unable to respond.

In 2003, NASA's twin Mars Exploration Rovers, Spirit and Opportunity, began exploring the surface of the red planet. While both rovers performed for longer than expected, Spirit's mission ended in 2009 when the rover became stuck in a soft patch of soil. Rovers can autonomously detect and avoid rocks and other obstacles with ease, but detecting soft soil hazards remains a challenge for rover operators. While Opportunity is still operating, it has lost mission time while stuck in soft soil patches.

The Autonomous Soil Assessment System 2.0 (ASAS), building upon previous work by Mission Control Space Services, will improve rovers' ability to navigate through unknown environments by detecting a much broader variety of terrains and hazard types through the use of artificial intelligence, and specifically deep learning techniques. ASAS can be employed to improve mission safety and efficiency in two ways: by running on ground station computers to help rover operators plan safe routes, or by operating in real time as a software payload onboard the rover to increase its autonomy by allowing it to handle hazard detection automatically.

Launching satellites is an expensive and unreliable process, yet demand for microsat launch services increases year after year.

Reaction Dynamics is pioneering a revolutionary, inherently safe type of propulsion system. This technology demonstration aims to develop the competencies necessary to use hybrid rocket engines in launch vehicles, and build and operate launch vehicles reliably. Additionally, other systems for supporting space launch operations, such as ground infrastructure, supply chains, avionics and communication systems, will be developed. Within this proposal, Reaction Dynamics hopes to launch the flight demonstration vehicle to an altitude of at least 100 km by early to mid-2020. Starting as early as 2023, the company aims to jump-start an orbital satellite launch service in Canada, targeting the emerging market of CubeSats, microsats as well as Earth observation missions.

Aerospace designers often use software that simulates complex electronic systems to evaluate the performance of different architectures and to refine software and hardware early in the development stage.

Heterogeneous computing systems (systems using more than one type of processor) offer advantages over homogenous systems in terms of speed and agility in processing, but aerospace simulation software has not yet been designed for computing systems with more than one processor. Space Codesign Systems proposes to develop a heterogeneous computing platform which will allow aerospace designers to more easily and efficiently design models of complex electronic systems, including those with embedded systems.