Meeting Artificial-Intelligence & Motion Planning on UAVs

Subject: Meeting Artificial-Intelligence & Motion Planning on UAVs
Faculties: Faculty of Industrial Engineering and Management
  Faculty of Aerospace Engineering
Researchers: Sagi Lefler, Ph.D Michael Katz, Victor Dweck, Ph.D Erez Karpas and Alexander Naidich

Abstract:

This study is concerned with mixed, bidirectional, composition of artificial-intelligence and motion-planning as applied to the cooperative decision and control of autonomous unmanned aerial vehicles (UAVs).

A scenario of interest is that of a team of UAVs cooperatively performing multiple tasks on multiple targets.

In this type of scenario there is a need of providing in real-time the UAV group with an assignment plan and the specific trajectories that each vehicle must follow under its dynamic constraints.

Thus, the high-level artificial intelligence (AI) mission planning problem is naturally coupled with the low-level motion planning problem of optimizing trajectories; making it one of the most challenging problems in cooperative autonomous multi-vehicle operation.

This multidisciplinary research focuses on developing novel methodologies for solving such coupled AI and motion planning problems.

The developed methods will be software incorporated and the system's complexity will be analyzed, both formally and empirically.

We expect that our synergetic approach will render the real-time solution of large-scale UAV cooperative decision and control problems feasible.