Leader-Follower Formation Control of Wheeled Mobile Robots without Attitude Measurements

The problem of leader-follower formation of a platoon of differential-drive wheeled mobile robots without using attitude measurements is addressed in this paper. Contrary to the position-distance approaches existing in the literature, the formation and collision avoidance is achieved by introducing a state-dependent delay in the desired trajectory. The delay is obtained as the output of a dynamical system and its magnitude will decrease/increase depending on the distance between the robots. To guarantee trajectory tracking and to overcome the lack of orientation measurements, an output feedback control and attitude observer are proposed based on the kinematic model of the robots. The attitude observer is designed directly on the special orthogonal group SO(2) and it can be used in open-loop schemes. The proposed control-observer scheme ensures asymptotic convergence of the tracking and observer errors. Finally, experimental results are presented to show the performance of the proposed approach.

Culturally Aware Social Robots That Carry Humans Inside Them, Protected by Defeasible Argumentation Systems

After taking note of the conceptual fact that robots may well carry humans inside them, and more specifically that modern AI-infused cars, jets, spaceships, etc. can be viewed as such robots, we present a case study in which inconsistent attitude measurements resulted in the tragic crash in Sweden of such a jet and the death of both pilots. After setting out desiderata for an automated defeasible inductive reasoner able to suitably prevent such tragedies, we formalize the scenario in a first-order defeasible reasoner—OSCAR—and find that it can quickly generate a partial solution to the dilemma the pilots couldn’t conquer. But we then note and address the shortcomings of OSCAR relative to the desiderata, and adumbrate a solution supplied by a more expressive reasoner based on an inductive defeasible multi-operator cognitive calculus (ℐ𝒟𝒞ℰ𝒞) that is inspired by a merely deductive (monotonic) precursor (𝒟𝒞ℰ𝒞). Our solution in this calculus exploits both the social and cultural aspects of of the jet/robot we suggest be engineered in the future. After describing our solution, some remarks about related prior work follow, we present and rebut two objections, and then wrap up with a brief conclusion.

Hidden religious aspects of job satisfaction and work attitudes: The differences between Eastern and Western Europe

This paper examines the links between religion and job satisfaction. Its concern is to compare Eastern and Western Europe. We use the 2015 International Social Survey Programme (ISSP) data covering both non-religious individuals and individuals affiliated to a religious denomination. While the Western European countries generally report significantly higher levels of job satisfaction compared to their Eastern counterparts, we test the hypothesis that religion also shows differentiated effects on job satisfaction and work attitudes. Our results indicate that religion has no significant effect on job satisfaction in either of the regions. In the West, religious affiliation has an influence on a larger variety of work attitude measurements compared to those in the East. In both regions, workers who regularly attend religious services would enjoy work significantly more even if they did not need money, consider high income as less important, and consider helping other people, contact with other people, and having a job useful to society as more important.

A Multi-Node Magnetic Positioning System with a Distributed Data Acquisition Architecture

We present a short-range magnetic positioning system that can track in real-time both the position and attitude (i.e., the orientation of the principal axes of an object in space) of up to six moving nodes. Moving nodes are small solenoids coupled with a capacitor (resonant circuit) and supplied with an oscillating voltage. Active moving nodes are detected by measuring the voltage that they induce on a three-dimensional matrix of passive coils. Data on each receiving coil are acquired simultaneously by a distributed data-acquisition architecture. Then, they are sent to a computer that calculates the position and attitude of each moving node. The entire process is run in real-time: the system can perform 62 position and attitude measurements per second when tracking six nodes simultaneously and up to 124 measurements per second when tracking one node only. Different active nodes are identified using a frequency-division multiple access technique. The position and angular resolution of the system have been experimentally estimated by tracking active nodes along a reference trajectory traced by a robotic arm. The factors limiting the viability of upscaling the system with more than six active nodes are discussed.

Two Supervised Machine Learning Approaches for Wind Velocity Estimation Using Multi-Rotor Copter Attitude Measurements

In this work we address the adequacy of two machine learning methods to tackle the problem of wind velocity estimation in the lowermost region of the atmosphere using on-board inertial drone data within an outdoor setting. We fed these data, and accompanying wind tower measurements, into a K-nearest neighbor (KNN) algorithm and a long short-term memory (LSTM) neural network to predict future windspeeds, by exploiting the stabilization response of two hovering drones in a wind field. Of the two approaches, we found that LSTM proved to be the most capable supervised learning model during more capricious wind conditions, and made competent windspeed predictions with an average root mean square error of 0.61 m·s−1 averaged across two drones, when trained on at least 20 min of flight data. During calmer conditions, a linear regression model demonstrated acceptable performance, but under more variable wind regimes the LSTM performed considerably better than the linear model, and generally comparable to more sophisticated methods. Our approach departs from other multi-rotor-based windspeed estimation schemes by circumventing the use of complex and specific dynamic models, to instead directly learn the relationship between drone attitude and fluctuating windspeeds. This exhibits utility in a range of otherwise prohibitive environments, like mountainous terrain or off-shore sites.

Saturated output feedback control for finite-time attitude stabilization of spacecraft

The finite-time attitude stabilization of spacecraft subject to actuator constraints and attitude measurements only is investigated. A saturated output feedback finite-time proportional-derivative control is proposed. Lyapunov stability theory and homogeneous method are employed to show the finite-time stabilization. Advantages of the proposed control include the finite-time stabilization featuring faster transient and higher precision and the absence of the modelling information and the velocity measurements in the control law formulation, and thus, it offers an easy-going solution for high-quality motion control of spacecraft. An additive feature is that the actuator saturation will not be reached by selecting the control gains a priori. Simulations are presented to illustrate the effectiveness of the proposed control.

The Evolving Field of Wind Energy Tourism: An Application of the Theory of Reasoned Action

Studies concerning adoption of wind energy tourism is growing in interest for academic researchers; however, the body of knowledge surrounding consumer adoption of wind farming as a tourism experience is still in its infancy. The enclosed study tests the applicability of the Theory of Reasoned Action (TRA) using that model's core constructs of behavioral beliefs, normative beliefs, subjective norms, and attitude measurements are predictors of action. The reported sample consisted of 287 Chinese residents who had visited China's Ningbo wind farm facility. By application of the factor analysis procedure, it was determined that behavioral beliefs, attitudes, subjective norms control, and normative beliefs exerted an interactive effect on resident intent to visit the Ningbo wind farm for recreational purposes. The prevailing message is that the need for social bonding, normative influences exerted by peers comprising environmental consciousness, and curiosity associated with the science behind wind farm technology serve as primary drivers of interest in wind farming for recreational purposes.