SS08: Robotic and AI Solutions for Smart Mobility
( CFP)

Session Code: a8uy6


  • Dr. Jianbo Lu
    Affiliation: Technical Expert, Ford Research and Innovation Center, Dearborn, Michigan 48124, USA

  • Dr. Dimitar Filev
    Affiliation: Technical Fellow, Ford Research and Innovation Center, Dearborn, Michigan 48124, USA

Scope and Goals

Current advancement in driverless cars, robotics, and artificial intelligence (AI) are some of the main drivers for smart mobility solutions that enable safe and efficient transportation, vehicle sharing, and reduced road congestions. Challenges include achieving full driving autonomy, integration of city infrastructure, vehicle on-board, and web resources in a unified transportation ecosystem, optimal use of all modes of travel, coverage of the first and last mile, and efficient automated delivery of goods in densely populated area. Regardless of the broad and diverse impact and applications aspects of smart mobility, their fundamentals are based on similar principles that are driven by the modern AI and robotic methods and techniques.

The goal of this special session is to provide a platform for sharing innovative approaches to solve challenging mobility problems and to apply the lessons learned to 2 different domains that can stimulate further research and development of related methods, algorithms, and tools.

Focus areas include advanced robotic and AI methods for perception, localization, motion planning, motion management and decision making, with applications to autonomous vehicles, delivery robots, personal mobility device, delivery drones, and the other transportation modalities of the broad field of smart mobility.


  • 16:00-18:00
    Dynamic Diffusion Maps-Based Path Planning for Real-Time Collision Avoidance of Mobile Robots (I)
    Hong Sanghyun, Ford Motor Company
    Lu Jianbo, Ford Motor Company
    Filev Dimitar, Ford Res. & Advanced Engineering