An optimal control strategy for collision avoidance of mobile robots in non-stationary environments

An optimal control formulation of the problem of collision avoidance of mobile robots in environments containing moving obstacles is presented. Collision avoidance is guaranteed if the minimum distance between the robot and the objects is nonzero. A nominal trajectory is assumed to be known from off-line planning. The main idea is to change the velocity along the nominal trajectory so that collisions are avoided. Furthermore, time consistency with the nominal plan is desirable. A numerical solution of the optimization problem is obtained. Simulation results verify the value of the proposed strategy

A computer architecture for intelligent machines

The Theory of Intelligent Machines proposes a hierarchical organization for the functions of an autonomous robot based on the Principle of Increasing Precision With Decreasing Intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed in recent years. A computer architecture that implements the lower two levels of the intelligent machine is presented. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Details of Execution Level controllers for motion and vision systems are addressed, as well as the Petri net transducer software used to implement Coordination Level functions. Extensions to UNIX and VxWorks operating systems which enable the development of a heterogeneous, distributed application are described. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems

Distance estimation and collision prediction for on-line robotic motion planning

An efficient method for computing the minimum distance and predicting collisions between moving objects is presented. This problem has been incorporated in the framework of an in-line motion planning algorithm to satisfy collision avoidance between a robot and moving objects modeled as convex polyhedra. In the beginning the deterministic problem, where the information about the objects is assumed to be certain is examined. If instead of the Euclidean norm, L(sub 1) or L(sub infinity) norms are used to represent distance, the problem becomes a linear programming problem. The stochastic problem is formulated, where the uncertainty is induced by sensing and the unknown dynamics of the moving obstacles. Two problems are considered: (1) filtering of the minimum distance between the robot and the moving object, at the present time; and (2) prediction of the minimum distance in the future, in order to predict possible collisions with the moving obstacles and estimate the collision time

The impact of corporate governance and corporate social responsibility on firms’ performance. Evidence from the US market.

The target of this study is to interpret the relation between factors that are not financial such as corporate governance, social responsibility and firms’ financial performance. The content of this research is of major interest as the role of sustainable finance has been vastly analyzed throughout the new millennium while firms’ performance is considered to be one of the most examined topics in the field of corporate finance. Recent literarure has focused on the significance of the sustainable finance based on the argument that, after the 2008 financial crisis, there is a major trend related to investors concerned about sustainable growth. Namely, a very large number of investors seeks to combine financial performance with positive social impact, by funding firms that actively contribute to sustainable development. This paper uses regression analysis (with year and industry effects) to find if there is any connection between the variables. Two data samples (All-industries data sample and Manufacturing industry data sample) have been used for the period of 2010-2016. Regarding all-industries data sample, the results show that there is a positive correlation between board size, social supply chain management, R&D expenditures and firms’ performance. On the other hand, executives compensation linked to better corporate governance/social responsibility is negatively correlated. I did not find any statistically significant connection between the percentage of independent directors, the percentage of women on board, CEO duality and financial performance. Moreover, as far as the secondary analysis (based on Manufacturing firms) is concerned, the results show that there is a positive relationship between CEO duality and firms’ profitability. Independent directors, R&D expenditures and social supply chain management are negatively connected. Here, no relationship found between the percentage of women on board, executives compensation linked to better corporate governance/social responsibility and financial performance. Finally, this dissertation underlines the importance of taking into consideration the effects of corporate governance and social responsibility where investors, stakeholders and corporations are considering sustainable growth and future development

Information-theoretic approach to the study of control systems

We propose an information-theoretic framework for analyzing control systems based on the close relationship of controllers to communication channels. A communication channel takes an input state and transforms it into an output state. A controller, similarly, takes the initial state of a system to be controlled and transforms it into a target state. In this sense, a controller can be thought of as an actuation channel that acts on inputs to produce desired outputs. In this transformation process, two different control strategies can be adopted: (i) the controller applies an actuation dynamics that is independent of the state of the system to be controlled (open-loop control); or (ii) the controller enacts an actuation dynamics that is based on some information about the state of the controlled system (closed-loop control). Using this communication channel model of control, we provide necessary and sufficient conditions for a system to be perfectly controllable and perfectly observable in terms of information and entropy. In addition, we derive a quantitative trade-off between the amount of information gathered by a closed-loop controller and its relative performance advantage over an open-loop controller in stabilizing a system. This work supplements earlier results [H. Touchette, S. Lloyd, Phys. Rev. Lett. 84, 1156 (2000)] by providing new derivations of the advantage afforded by closed-loop control and by proposing an information-based optimality criterion for control systems. New applications of this approach pertaining to proportional controllers, and the control of chaotic maps are also presented.Comment: 18 pages, 7 eps figure