Guidance system

About: Guidance system is a research topic. Over the lifetime, 4282 publications have been published within this topic receiving 45964 citations.

Systems and methods for dynamic planning and operation of autonomous systems using image observation and information theory

Abstract: Systems and methods described herein incorporate autonomous navigation using a vision-based guidance system. The vision-based guidance system enables autonomous trajectory planning and motion execution by the described systems and methods without feedback or communication with external operators. The systems and methods described herein can autonomously track an object of interest while seeking to obtain a diversity of views of the object of interest to aid in object identification. The systems and methods described include a robust reacquisition methodology. By handling navigation and tracking autonomously, systems described herein can react more quickly to non-cooperative moving objects of interest and can operate in situations where communications with external operators is compromised or absent.

Mass transportation passenger guidance system

Abstract: Device for guiding flows of individuals in mass transportation systems, containing at least the following components: A) a guidance system in embarking and disembarking areas interacting with at least one of the following devices: a) a guidance system in the means of transportation, b) a blocking device between the embarking/disembarking areas and the means of transportation.

A real-time guidance system for an autonomous vehicle

Abstract: A real-time system for the control of an autonomous vehicle consisting of a nested hierarchy of control modules is described. The focus is on the PILOT module which provdies the real-time guidance of the system. It is responsible for the generation and tracking of dynamically feasible trajectories which follow the generally planned path and avoid local obstacles. The PILOT operation is based on a combination of simple rules and heuristic search. The state space consists of two parts: the lower level state space which represents the model of the world as a set of relationships among the units of vehicle state variables representing steering, acceleration, and velocity, as well as positions of obstacles, and the upper level state space where the relationships among generalized objects are represented as rules. Rules provide simple elementary maneuvers, and are applied when the upper level situation is easily recognized. Otherwise the situations are handled by the lower level search. Example runs of the vehicle are simulated to demonstrate the complexity of behavior. The algorithm has also been tested on a gas powered dune buggy developed at Drexel University.

Digital Elevation Map estimation by vision-lidar fusion

Abstract: This paper is about environment perception for navigation system in real outdoor applications. Unlike other approaches that try to detect an obstacle of binary state, we consider here a Digital Elevation Map (DEM). This map has to be built in regards to the guidance system's needs. These needs depend on the vehicle capabilities, its dynamical constraints, its speed etc… Starting with the navigation system's needs, we establish a perception strategy to fill the DEM the most accuratly possible. This stategy allows to efficiently improve perception capability (sensors and computation capabilities) of our robot. Then, we proposed a system based on this perception strategy by the combinaison of vision and rangefinder.

Inertial navigational guidance system for a driverless vehicle utilizing laser obstacle sensors

Abstract: A navigational control system for, and method of controlling the operation of, a driverless vehicle. The system includes a vehicle travel path and a visual object detection system for generating data relating to the position of the vehicle relative to objects in readable proximity to the travel path. The system includes an inertial guidance system for controlling operation of steering and drive mechanisms to direct the vehicle substantially along the travel path, and for correcting deviation from said travel path based upon data generated by said visual object detection systems, and for detecting impending obstacle contact.