A Review of Intelligent Systems Software for Autonomous Vehicles

Abstract

The need for intelligent unmanned vehicles has been steadily increasing. These vehicles could be air-, ground-, space-, or sea-based. This paper will review some of the most common software systems and methods that could be used for controlling such vehicles. Early attempts at mobile robots were confined to simple laboratory environments. For vehicles to operate in realworld noisy and uncertain environments, they need to include numerous sensors and they need to include both reactive and deliberative features. The most effective software systems have been hierarchical or multi-layered. Many of these systems mimic biological systems. This paper reviews several software approaches for autonomous vehicles. While there are similarities, there are differences as well. Most of these software systems are very difficult to use, and few of them have the ability to learn. Autonomous vehicles promise remarkable capabilities for both civilian and military applications, but much work remains to develop intelligent systems software which can be used for a wide range of applications. In particular there is a need for reliable open-source software that can be used on inexpensive autonomous vehicles.

Autonomic element based architecture for unmanned underwater vehicles

“…These include unmanned spacecraft (US), unmanned air vehicles (UAVs), unmanned ground vehicles (UGVs), and unmanned underwater vehicles (UUVs) [1]. UUVs share common control problems with US, UAVs, and UGVs except for the limitation of communication in an underwater environment.…”

Steering Behaviour for Computer based Intelligent Agents

“…A more interesting approach would be to retain steering direction state and make small random displacements to it each frame. Thus for each frame it would have radically different behaviour [8]. The steering force takes a random run from one direction to another.…”

“…Real vehicles cannot do this and in any case they need undesirably large changes in orientation during a single time step. This problem can be solved by placing few additional constraint like a change of orientation [8,9], or by limiting the lateral steering component at low speeds, or by simulating moment of inertia.…”

An Intelligent Controller for Collaborative Unmanned Air Vehicles

“…There are many different approaches to intelligent control. A few of them are described in references [2]- [5]. There is no universal consensus on how to define or measure an intelligent system.…”