Grant: CCI Applied Research and Development Grants
Humber College Institute of Technology and Advanced Learning
$40,000.00
Enhancing LocoMobi Mobi 1: A Comprehensive Study and Optimization of Robot Navigation and Safety – Phase 2
EF 2024-25
Résumé
This project aims to revolutionize Mobi, LocoMobi World Inc’s (LocoMobi) existing operational parking robot, into the cornerstone of a fully automated, secure, and efficient parking operation. As automation continues to reshape parking infrastructures globally, the demand for autonomous mobile parking enforcement robots has surged. While Canada currently lacks such technology, the worldwide landscape is witnessing a rapid adoption of automated solutions to address parking challenges. In an article for the Canadian Parking Association, Shawn Walker (2016) states that the parking sector will be significantly impacted by robotics, artificial intelligence, and autonomous vehicles in the future. LocoMobi, a Smart City technology small and medium-sized enterprise (SME) headquartered in Mississauga, Ontario, is at the forefront of this transformation. Specializing in diverse and innovative enterprise hardware and cloud-based software offerings for parking, tolling, transit, storage, asset tracking, and threat management sectors, LocoMobi customizes solutions tailored to specific Smart City needs. Recently, LocoMobi and Humber completed the first phase small-scale test bench project of autonomous vehicles with 3D LiDAR mapping made possible by Greenfield Research and Innovation Funds supported by Humber’s NSERC Mobilize grant. By harnessing advanced technologies, this collaborative effort promises to elevate the user experience and set new standards in parking automation. The engagement and cooperation between LocoMobi and Humber College are crucial in realizing a parking solution that seamlessly integrates innovation, security, and efficiency. Toward the project's culmination, the objective is to deliver a Minimum Viable Product (MVP) that Locomobi can leverage for commercialization. The MVP should achieve the following requirements: 1) a Fully Autonomous drive vehicle with manual remote control; 2) Mapping and navigation by avoiding object features using current edge technologies; 3) Light and sound systems to show or communicate various scenarios during operation, and 4) Take a picture of the license plate and process it from a safe distance.
Programme
CCI Applied Research and Development Grants
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
CCARD-2023-00982
Name nom
Garcia, Juan Felipe
Department département
Office of Research and Innovation - Humber College (Humber College Institute of Technology and Advanced Learning)
Organization id
1662
Institution établissement
Humber College Institute of Technology and Advanced Learning
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2023
Award amount
40000
Program id
CCARD
Program name en
CCI Applied Research and Development Grants
Program name fr
ICC Subventions de recherche et développement appliquée
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
nan
Area of application code
9999
Area of application group en
Not available
Area of application group fr
Non disponible
Area of application en
Not available
Area of application fr
Non disponible
Research subject code
9999
Research subject group en
Not available
Research subject group fr
Non disponible
Research subject en
Not available
Research subject fr
Non disponible
Field of research list codes
RDF2030103
Field of research list names en
Middleware systems
Field of research list names fr
Systèmes intergiciels
Socioeconomic objective list codes
RDS10608
Socioeconomic objective list names en
Machinery and equipment (including automated machinery and equipment)
Socioeconomic objective list names fr
Machines et matériel (y compris les machines et le matériel automatisés)
Application title
Enhancing LocoMobi Mobi 1: A Comprehensive Study and Optimization of Robot Navigation and Safety – Phase 2
Keywords
Minimum Viable Product ; Smart City Technologies; Automated Guided Vehicles; LiDAR Mapping; Autonomous Mobile Parking Enforcement
Application summary
This project aims to revolutionize Mobi, LocoMobi World Inc’s (LocoMobi) existing operational parking robot, into the cornerstone of a fully automated, secure, and efficient parking operation. As automation continues to reshape parking infrastructures globally, the demand for autonomous mobile parking enforcement robots has surged. While Canada currently lacks such technology, the worldwide landscape is witnessing a rapid adoption of automated solutions to address parking challenges. In an article for the Canadian Parking Association, Shawn Walker (2016) states that the parking sector will be significantly impacted by robotics, artificial intelligence, and autonomous vehicles in the future. LocoMobi, a Smart City technology small and medium-sized enterprise (SME) headquartered in Mississauga, Ontario, is at the forefront of this transformation. Specializing in diverse and innovative enterprise hardware and cloud-based software offerings for parking, tolling, transit, storage, asset tracking, and threat management sectors, LocoMobi customizes solutions tailored to specific Smart City needs. Recently, LocoMobi and Humber completed the first phase small-scale test bench project of autonomous vehicles with 3D LiDAR mapping made possible by Greenfield Research and Innovation Funds supported by Humber’s NSERC Mobilize grant. By harnessing advanced technologies, this collaborative effort promises to elevate the user experience and set new standards in parking automation. The engagement and cooperation between LocoMobi and Humber College are crucial in realizing a parking solution that seamlessly integrates innovation, security, and efficiency. Toward the project's culmination, the objective is to deliver a Minimum Viable Product (MVP) that Locomobi can leverage for commercialization. The MVP should achieve the following requirements: 1) a Fully Autonomous drive vehicle with manual remote control; 2) Mapping and navigation by avoiding object features using current edge technologies; 3) Light and sound systems to show or communicate various scenarios during operation, and 4) Take a picture of the license plate and process it from a safe distance.
