Multiresolutional models of uncertainty generation and reduction

Kolmogorov's axiomatic principles of the probability theory, are reconsidered in the scope of their applicability to the processes of knowledge acquisition and interpretation. The model of uncertainty generation is modified in order to reflect the reality of engineering problems, particularly in the area of intelligent control. This model implies algorithms of learning which are organized in three groups which reflect the degree of conceptualization of the knowledge the system is dealing with. It is essential that these algorithms are motivated by and consistent with the multiresolutional model of knowledge representation which is reflected in the structure of models and the algorithms of learning

Techniques and potential capabilities of multi-resolutional information (knowledge) processing

A concept of nested hierarchical (multi-resolutional, pyramidal) information (knowledge) processing is introduced for a variety of systems including data and/or knowledge bases, vision, control, and manufacturing systems, industrial automated robots, and (self-programmed) autonomous intelligent machines. A set of practical recommendations is presented using a case study of a multiresolutional object representation. It is demonstrated here that any intelligent module transforms (sometimes, irreversibly) the knowledge it deals with, and this tranformation affects the subsequent computation processes, e.g., those of decision and control. Several types of knowledge transformation are reviewed. Definite conditions are analyzed, satisfaction of which is required for organization and processing of redundant information (knowledge) in the multi-resolutional systems. Providing a definite degree of redundancy is one of these conditions

Coordination in a hierarchical multi-actuator controller

A hierarchical multi-actuator controller is represented as a multi-resolutional information (knowledge) system utilizing a number of intelligent modules with decision making capabilities. The laws of multi-resolutional information (knowledge) organization and processing are presumed to be satisfied including the rules of dealing with redundant knowledge. A general case is considered in which a process to be controlled by a multiplicity of actuators is a distributed one and the condition of distribution can be formulated analytically. Operation of a lumped multi-actuator process is a particular case which has a broad practical application

A genetic technique for planning a control sequence to navigate the state space with a quasi-minimum-cost output trajectory for a non-linear multi-dimnensional system

There are many multi-stage optimization problems that are not easily solved through any known direct method when the stages are coupled. For instance, we have investigated the problem of planning a vehicle's control sequence to negotiate obstacles and reach a goal in minimum time. The vehicle has a known mass, and the controlling forces have finite limits. We have developed a technique that finds admissible control trajectories which tend to minimize the vehicle's transit time through the obstacle field. The immediate applications is that of a space robot which must rapidly traverse around 2-or-3 dimensional structures via application of a rotating thruster or non-rotating on-off for such vehicles is located at the Marshall Space Flight Center in Huntsville Alabama. However, it appears that the development method is applicable to a general set of optimization problems in which the cost function and the multi-dimensional multi-state system can be any nonlinear functions, which are continuous in the operating regions. Other applications included the planning of optimal navigation pathways through a transversability graph; the planning of control input for under-water maneuvering vehicles which have complex control state-space relationships; the planning of control sequences for milling and manufacturing robots; the planning of control and trajectories for automated delivery vehicles; and the optimization and athletic training in slalom sports

A snake-based scheme for path planning and control with constraints by distributed visual sensors

YesThis paper proposes a robot navigation scheme using wireless visual sensors deployed in an environment. Different from the conventional autonomous robot approaches, the scheme intends to relieve massive on-board information processing required by a robot to its environment so that a robot or a vehicle with less intelligence can exhibit sophisticated mobility. A three-state snake mechanism is developed for coordinating a series of sensors to form a reference path. Wireless visual sensors communicate internal forces with each other along the reference snake for dynamic adjustment, react to repulsive forces from obstacles, and activate a state change in the snake body from a flexible state to a rigid or even to a broken state due to kinematic or environmental constraints. A control snake is further proposed as a tracker of the reference path, taking into account the robot’s non-holonomic constraint and limited steering power. A predictive control algorithm is developed to have an optimal velocity profile under robot dynamic constraints for the snake tracking. They together form a unified solution for robot navigation by distributed sensors to deal with the kinematic and dynamic constraints of a robot and to react to dynamic changes in advance. Simulations and experiments demonstrate the capability of a wireless sensor network to carry out low-level control activities for a vehicle.Royal Society, Natural Science Funding Council (China

Design parameters for adjusting the visual field of binocular stereo cameras

[EN] Stereoscopic cameras are becoming fundamental sensors for providing perception capabilities for automated vehicles; however, they need to be adequately setup to avoid excessive data processing and unreliable outcomes. Combinations of baselines and lens focal lengths were optimised to adjust the field of view of a stereo camera to provide the two fundamental perceptions required for intelligent vehicles: safeguarding distances around 6 m and look-ahead distances up to 20 m for automatic guidance. The main objective was to develop a systematic procedure to find the parameters that best sense the desired field of view. Quantitative indices to estimate perceptive quality, such as relative errors and efficiencies, were defined and applied to particular cases. Experiments, both in the laboratory and outdoor, led to the conclusion that short ranges under 6 m from the vehicle were best acquired with 8 mm lenses and baselines ranging from 100 mm to 150 mm, whereas 200 mm baselines coupled with 12 mm and 8 mm lenses were more suitable for longer look-ahead distances. These experiments also proved the utility of the methodology proposed. ª 2009 IAgrE. Published by Elsevier Ltd. All rights reserved.The material presented in this paper was based upon work supported partially by the Ministry of Education and Science Funds, Spain (AGL2006-09656/AGR), the United States Department of Agriculture (USDA) Hatch Funds (ILLU-10-352 AE) and Bruce Cowgur Mid-Tech Memorial Funds. Any opinions, findings, and conclusions expressed in this publication are those of the authors and do not necessarily reflect the views of the University of Illinois, USA; the Ministry of Education and Science, Spain; the USDA, USA; and Midwest Technologies Inc., USA.Rovira Más, F. (2010). Design parameters for adjusting the visual field of binocular stereo cameras. Biosystems Engineering. 105(1):59-70. https://doi.org/10.1016/j.biosystemseng.2009.09.013S5970105

Autonomous mobile robots : vehicles with cognitive control

xix, 580 p. : ill. ; 23 cm