All publications

Risk-Aware Emergency Landing Planning for Gliding Aircraft Model in Urban Environments

  • DOI: 10.1109/IROS55552.2023.10341622
  • Link: https://doi.org/10.1109/IROS55552.2023.10341622
  • Department: Department of Computer Science, Artificial Intelligence Center
  • Annotation:
    An in-flight loss of thrust poses a risk to the aircraft, its passengers, and people on the ground. When a loss of thrust happens, the (auto)pilot is forced to perform an emergency landing, possibly toward one of the reachable airports. If none of the airports is reachable, the aircraft is forced to land at another location, which can be risky in urban environments. In this work, we present a generalization of the previous work on planning safe emergency landing in the case of in-flight loss of thrust such that the risk induced by the loss of thrust can be assessed if none of the airports are reachable. The proposed method relies on planning space discretization and efficient risk propagation through the risk map. The approach can find the least risky landing site and corresponding forced landing trajectory for any configuration in the planning space. The method has been empirically evaluated in a realistic urban scenario. The results support its suitability for risk-aware planning of an emergency landing in the case of in-flight loss of thrust.

Finding 3D Dubins Paths with Pitch Angle Constraint Using Non-linear Optimization

  • DOI: 10.1109/ECMR50962.2021.9568787
  • Link: https://doi.org/10.1109/ECMR50962.2021.9568787
  • Department: Artificial Intelligence Center
  • Annotation:
    This paper presents a novel non-linear programming formulation to find the shortest 3D Dubins path with a limited pitch angle. Such a path is suitable for fix-wing aircraft because it satisfies both the minimum turning radius and pitch angle constraints, and thus it is a feasible and smooth path in the 3D space. The proposed method utilizes the existing decoupled approach as an initial solution and improves its quality by dividing the path into small segments with constant curvature. The proposed formulation encodes the path using the direction vectors that significantly reduce the needed optimization variables. Therefore, a path with 100 segments can be optimized in about one second using conventional computational resources. Although the decoupled paths are usually within 2 % from the lower bound, the proposed approach further reduces the gap by about 30 %.

Responsible person Ing. Mgr. Radovan Suk