Autonomous system (mathematics)

About: Autonomous system (mathematics) is a research topic. Over the lifetime, 1648 publications have been published within this topic receiving 38373 citations.

Design and parametric control of co-axes driven two-wheeled balancing robot

Abstract: Robots can be seen in our daily life. Recently, robotic applications and their wide range of functionalities have drawn many engineers’ attentions. Two-wheeled balancing robots are typical example of autonomous robots that are basically unstable and free to fall forward or backward. Using only two wheels for these types of robot provide lighter weight and smoother maneuver. A physical robot was designed and built. Then robot’s specifications were observed for mathematical modeling and simulation. Lagrangian approach was used to generate the ordinary differential equations (ODEs) of system. An initial assumption was made to linearize the system and state-space model of system was developed. A full state feedback (FSF) control was designed to stabilize the unstable system. There are some robot’s characteristics that are directly engaged with behavior of system. Therefore, parameter studies were done to choose the right constants to optimize the system’s performance. Sensors were calibrated before integrating with robot and microcontroller was programmed to implement the control unit.

Autonomous Knowledge-Based Navigation in an Unknown Two-Dimensional Environment with Convex Polygon Obstacles

Abstract: Navigation of autonomous vehicles in environments where the exact locations of obstacles are initially know has been the focus of research for two decades. More recently, algorithms for controlling progress through unknown environments have been proposed. The utilization of knowledge-based systems for studying the behavior of an autonomous vehicles presents new challenges for research. A knowledge-driven autonomous system simulation was developed which enabled an autonomous mobile system to move in a two-dimensional, obstacle strewn, environment and to use a simulated ranging/vision sensor to test whether a selected goal position was visible or whether the goal was obscured by one or more of the polygon obstacles. As the mobile system gained information about the location of obstacles, that knowledge is added to the system's knowledge-base. High-level navigation rules were fired when necessary conditions in the knowledge base existed. The necessary low-level computations (eg., vertex visibilities, etc) were, when required within the context of a selected rule, carried or' through appropriate Lisp functions. The knowledge-based program was implemented in the generalized decision-making paradigm, OPS5.

Increasing the trafficability of unmanned ground vehicles through intelligent morphing

Abstract: Unmanned systems are used where humans are either unable or unwilling to operate, but only if they can perform as good as, if not better than us. Systems must become more autonomous so that they can operate without assistance, relieving the burden of controlling and monitoring them, and to do that they need to be more intelligent and highly capable. In terms of ground vehicles, their primary objective is to be able to travel from A to B where the systems success or failure is determined by its mobility, for which terrain is the key element. This paper explores the concept of creating a more autonomous system by making it more perceptive about the terrain, and with reconfigurable elements, making it more capable of traversing it.