Imagine some of the difficult driving conditions experienced by vehicle operators. In these conditions, the sun might be blindingly bright, or the snow might obfuscate what is going on around the vehicle. Surprisingly, the sensors used by autonomous vehicles to understand the environment they are in suffer from similar effects. As a field, robotics has yet to tackle integrity monitoring of the sensors used in autonomous applications.
Additive manufacturing, also called 3D printing, of composites can manufacture final parts with high strength and stiffness. In this project, carbon fiber composites with a high temperature polymer are used for 3D printing. A custom 3D printing head installed on a robotic arm is used for manufacturing. Specimens are 3D printed to evaluate structural and thermal properties of final parts. Automated manufacturing of composites using robotic 3D printing is efficient for fabricating small-scale parts with low volume and can open new opportunities for composites.
Autonomous vehicles must be constantly aware of all aspects of the driving environment, and so are typically designed with both omni-directional and long-range forward sensor footprints. The ability to accurately detect, track and predict the motion of distant vehicles and pedestrians along the driving route remains a significant challenge, for today’s state of the art perception methods, however, despite ever-more complex network designs and ever-better sensor configurations.
A novel design of football helmet to mitigate the concussion is proposed here. The jerk transferred to brain, due to the collisions between players and due to falling on the field, will be reduced, attenuated, decomposed, and directed away from reaching the brain. Multi-shell made of composite materials, along with speed-dependent padding between head and inner shell will be used. Relative motion between shells will be attained though a specially designed structure made of strong material bars. Therefore, the force of collisions will be controlled by a number of safety layers.
Additive manufacturing (AM), 3D printing, offers flexibility in manufacturing and can process a wide range of materials. In this project, polymers and composites are investigated to increase mechanical performance, and to reduce weight, cost, and lead time of candidate parts. Pratt & Whitney Canada (P&WC) can greatly benefit from AM processes in aircraft engine components. In addition, AM can shorten the engine design cycle, and Research and Development (R&D) activities. This requires investigation of 3D printed parts and the impact of manufacturing parameters on final part properties, e.g.
Cameras are a fundamental component of modern robotic systems. As robots have become relied upon for safety-critical tasks, the need for robust sensing is apparent. Cameras have a major limitation, compared to other sensors such as LIDAR, in high-dynamic-range environments where lighting conditions rapidly change. These changes can cause visual navigation algorithms to struggle and, in some cases, fail in instances where images become severely under- or overexposed.
The main purpose of this project is to develop an enhanced portable ground Control Station (GCS) equipped with an Advanced Stand-Alone Virtual Reality Head Mounted Display (ASVR-HMD). In the beginning, a Commercial-off-the-shelf (COTS) stand-alone Virtual Reality (VR) headset would be connected to the flight simulation tool. The VR HMD will be used to visualize basic flight simulation. Then, an onboard camera would be integrated to the aircraft provided by the partner organization.
On time discovery of problems and constant monitoring of construction sites have great economical benefit. It requires the capability of highly efficient and accurate object detection and segmentation algorithms that can work with coarsely labelled training samples. The project is aimed to develop new learning-based object detection and segmentation algorithms for problem detection and mapping of construction sites with high accuracy and efficiency. This project will improve operation efficiency for construction related projects.
The proposed research will involve optimizing and improving engineering operations within Bombardier based on data collected from flight recorders and aircraft operators. This will involve developing new processes in maintenance tracking (i.e. tracking aftermarket spares sales, scheduled maintenance, accessing direct maintenance costs per component, etc.), and implementation of a stress tools suite for in-service structures evaluations. Currently, many internal processes within Bombardier are based on nonstandardized reporting and data collection methods.
Drone Delivery Canada (DDC) designs and operates high performance Remotely Piloted Aerial Systems (RPAS) to deliver payloads between depots and warehouses. The DDC engineering department is looking to design and deploy a ground-based system to track and point at the Remotely Piloted Aerial Vehicle (RPAV) during flight in real-time.