We are an interdisciplinary initiative at Queen’s University focused on combining Artificial Intelligence, Robotics, and Human Machine Interaction to create future intelligent systems and robotic machines that enhance human productivity, safety, performance, and quality of life.
As a teaching strategy, simulation-based training has been around a long time. From aviation and space flight to the military, from law to policing, simulation has been used to create learning environments that reflect the real world, without putting the learner or other participants at risk. A multidisciplinary group of faculty and post-doctoral researchers from …
This project will mainly explore streaming multi-modal Knowledge Base Population (KBP) problems by considering both text and images. We expect to propose novel ideas that may help Alibaba’s technical challenges. Specifically, we aim to identify entities using both unstructured text data (e.g., image descriptions) and the corresponding images. The aim is that, by creating models …
The goal of this project is to develop deep-learning based algorithms for identifying near-duplicates in a large collection of bug reports. Project tasks will consist of the following: Providing expert advice on the best deep-learning approaches to use for solving EA’s bug de-duplication problem. Designing, testing, and evaluating deep-learning algorithms to solve the bug deduplication …
In Canada, thermal stress buildup due to climatic changes can lead to failure of rail structures. Currently, there are no techniques available to continuously monitor the stress state in a rail over long distances. Distributed fibre optic sensing is a promising solution. Due to the extent of rail track infrastructure in Canada (45,000 km), the …
Ambient factors such as light, heat, and music can significantly impact physical comfort in employees. Additionally, affective states and cognitive load of workplace occupants can affect their quality of life, general happiness, and cognitive capacity. This research aims to design and develop a smart workplace capable of detecting, analyzing, and acting on the environmental ambient …
Dr. Xiaodan Zhu from Ingenuity Labs is partnering with Dr. Samuel Dahan from the Queen’s Faculty of Law on an intelligent dispute resolution system that evens the playing field for self-represented litigants in employment, trademark, and personal injury disputes by offering them data-driven predictions, based on case law trends and negotiation data from thousands of …
Virtual Reality (VR) has the ability to immerse users in a simulated environment and provide them with experiential learning opportunities. Most undergraduate Chemical Engineering students are required to design a chemical plant for their capstone design project without ever having visited or interacted with a full-scale processing plant. This project will design and develop an …
With smart and autonomous vehicles around the corner, significant advances are being made in integration of sensing, machine learning, and advanced control systems in vehicles. Modern vehicles currently contain 60-100 sensors on average, and this number is expected to rise to 200 sensors per car by 2020. These sensing technologies, however, are mostly aimed at …
This research program is a multi-disciplinary partnership between the City of Kingston and Ingenuity Labs that will investigate robotic inspection technologies as an integral step towards turning the Kingston Third Crossing into a smart structure. The goal of this proposed research program is to begin development of a high resolution digital image analysis and artificial …
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 …