Intelligent Autonomous Systems: Dynamics, Control, and Navigation
Professor: Jinjun Shan
Contact Info: jjshan@yorku.ca
Lab Website: https://lassonde.yorku.ca/users/jjshan
Position Type: Lassonde Undergraduate Research Award (LURA); NSERC Undergraduate Student Research Award (USRA)
Open Positions: 2
Project Description: An Autonomous System is an agent or system composed of a machine being driven or controlled by some form of autonomy. Autonomous systems are broadly prevalent in many sectors, from manufacturing, agriculture, traffic control, urban security, electric grids, to the medical industry. Autonomous systems always interact with humans while they are replacing humans in a variety of tasks, and in the years to come, such systems will become central and crucial to human life. While the field of autonomous unmanned vehicles has made tremendous progress over the last years, many questions remain unanswered. The increased popularity of data-driven algorithms in both perception systems and planning systems requires a second wave of innovation; verifiability, safety, and explainability are key requirements to allow the transition from systems suitable for showcases toward production-ready autonomous vehicles in our everyday lives. Additionally, autonomous systems that operate in complex, dynamic, and interactive environments require artificial intelligence that generalizes to unpredictable situations and reasons in a timely manner about the interactions with many traffic participants. Autonomous systems still need to reach human-level reliability in decision-making, planning, and perception, and current detection and segmentation accuracies do not yet suffice in difficult conditions, such as inclement weather. In recent years, Prof. Shan’s SDCNLab at York University has been working toward the advancement of some essential technologies (cooperative control; high-precision navigation and positioning; optimal motion planning and decision-making) in autonomous systems, specifically within the context of engineering applications, such as autonomous transportation, self-driving, collaborative mapping, etc. We are looking for undergraduate engineering students to work with graduate students and research fellows on (a) programming; (b) hardware design and development; (c) experimental validation. Through these activities, students will gain experience in control and navigation system design, hardware, and software development, etc. These experiences will be very helpful for the student’s future study and work.
Duties and Responsibilities: The successful student will be working with graduate students and research fellows on (a) programming; (b) hardware development and implementation. Through these activities, the student will gain experience in control and navigation system design, hardware, and software development, etc. These experiences will be very helpful for the student’s future study and work.
Desired Technical Skills:
- Good programming skills, MATLAB, C, and Linux
- Enrolled in engineering degree
- Familiar with ROS
- Team player.
Desired Course(s): Senior engineering or computer science students.
Space Asset Simulation
Professor: Regina Lee
Contact Info: REGINAL@yorku.ca
Lab Website: https://nanosatellite.lab.yorku.ca
Position Type: Lassonde Undergraduate Research Award (LURA); NSERC Undergraduate Student Research Award (USRA)
Open Positions: 1
Project Description:
1) Asset Definition and Simulation Period- Define the parameters and characteristics of the space assets to be simulated. Limit the simulation period to one month.
2) Report on Orbit Propagators to assess the impact of different orbit propagators on the accuracy of orbit predictions. Generate a report comparing the 7-day propagated orbit positions using various orbit propagators against the High-Precision Orbit Propagator (HPOP). Highlight differences in the positions and analyze the accuracy of each propagator..
Duties and Responsibilities: Generate an STK scenario for a proposed SSA mission and present a full report on mission analysis.
Desired Technical Skills:
Software skills. Basic understanding of orbit dynamics and spacecraft attitude control.
Quantification of Forest Above-ground Biomass (AGB) Using Advanced Remotely Sensed Data
Professor: Baoxin Hu
Contact Info: baoxin@yorku.ca
Lab Website: https://eo.lab.yorku.ca/
Position Type: Lassonde Undergraduate Research Award (LURA); NSERC Undergraduate Student Research Award (USRA)
Open Positions: 1
Project Description: Information about forest above-ground biomass (AGB) is crucial to assess natural climate solutions to reduce carbon emissions, support biodiversity conservation, and improve forest resilience in a changing climate. Despite substantial efforts, it remains challenge to accurately, efficiently, and reliably quantify AGB. In this project, we will develop an end-to-end process to estimate AGB at the locale scale using high-density LiDAR data for carbon credit verification.
Duties and Responsibilities:
(1) Conduct literature review on existing methods
(2) Process in-situ data for calibration and validation purpose
(3) Process LiDAR data
(4) Improve in-house algorithms for tree species classification
(5) Write technical reports.
Desired Technical Skills:
Programming skills in R or python
familiar with GIS software
Desired Course(s):
1. Second/third/fourth students in Physical Geography, Geomatics, Computer Science, Mathematics, or related Science and Engineering disciplines.
2. Experience with data/image analysis
Other desired qualifications or considerations: Experience with machine learning and deep learning is preferred.
Quantification of forest integrity using advanced remotely sensed data
Professor: Baoxin Hu
Contact Info: baoxin@yorku.ca
Lab Website: https://eo.lab.yorku.ca/
Position Type: Lassonde Undergraduate Research Award (LURA); NSERC Undergraduate Student Research Award (USRA)
Open Positions: 1
Project Description: This project aims to develop individual tree-based artificial intelligence (AI)-driven solutions to accurately quantify forest vegetation and its ecological integrity by addressing the three pillars of forest ecological integrity—structures, composition, and functions individually and holistically and by integrating Indigenous knowledge of forest ecosystems.
Duties and Responsibilities:
(1) Conduct literature review on existing methods on the indictors of forest integrity and their measure.
(2) Process in-situ data and generate labelled data for training and validation purpose.
(3) Process remotely sensed data including UAV-based and airborne LiDAR data, and satellite imagery.
(4) Exploit the use of LiDAR data in understory mapping.
(5) Attend regular project meetings and give presentations.
(6) Write a technical report and assist in a journal publication.
Desired Technical Skills: Strong programming skills in R or python.
Desired Course(s):
1. Second/third/fourth year students in Physical Geography, Geomatics, Computer Science, Mathematics, or related Science and Engineering disciplines.
2. Experience with data/image analysis.
Other Desired Qualifications: Self-motivated, team player.
Spacecraft Testbeds and On-Orbit Robotics
Assistive Robotics for Aging in Place
Professor: Michael C.F. Bazzocchi
Contact Info: mbazz@yorku.ca
Lab Website: https://www.astrolabresearch.com/
Position Type: Lassonde Undergraduate Research Award (LURA); NSERC Undergraduate Student Research Award (USRA)
Open Positions: 1
Project Description: Currently, the Astronautics and Robotics Laboratory (ASTRO Lab) is seeking students for research projects in the data collection and development of assistive technologies for aging adults under the supervision of Prof. Michael Bazzocchi. Students will be engaged in projects related to data processing, motion capture, biomechanics, ergonomics, computer vision, assistive technologies, assistive robotics, device fabrication, and participant trials. For more information about the lab and associated projects, please refer to https://www.astrolabresearch.com/
Duties and Responsibilities: Specific student project details are determined based on the students’ expertise as well as their research and professional goals. Generally, students are expected to formulate clear research objectives, perform a literature review to gain a working understanding in their research areas, construct a clear methodology and/or test procedure for their research and experiments, conduct simulations, fabricate prototypes, and conduct experiments, and document their research in formal technical reports or manuscripts for publication.
Desired Technical Skills: Students with some experience in the following areas are especially encouraged to apply: biomechanics, computer vision, robotics, aging, and assistive technologies. Applicants should have proficiency in technical writing and experience in computer programming, CAD experience is an asset.
Desired Course(s): Biomechanical or Robotics Engineering (or similar).
Other Desired Qualifications: Applicants with interests in long-term research projects or in other projects within the ASTRO Lab research areas are also encouraged to apply.