Neural preprocessing and control of reactive walking machines

Research in the domain of biologically inspired walking machines has focused for the most part on the mechanical designs and locomotion control. Although some of this research has been concentrated on the generation of a reactive behavior of walking machines, it has been restricted only to a few of such reactive behaviors. However, from this research, there are only few examples where different behaviors have been implemented in one machine at the same time. In general, these walking machines were solely designed for pure locomotion, i.e. without sensing environmental stimuli. <p> Therefore, in this thesis, biologically inspired walking machines with different reactive behaviors are presented. Inspired by obstacle avoidance and escape behavior of scorpions and cockroaches, such behavior is implemented in the walking machines as a negative tropism. On the other hand, a sound induced behavior called “sound tropism”, in analogy to the prey capture behavior of spiders, is employed as a model of a positive tropism. The biological sensing systems which those animals use to trigger the described behaviors are investigated so that they can be reproduced in the abstract form with respect to their principle functionalities. In addition, the morphologies of a salamander and a cockroach which are designed for efficient locomotion are also taken into account for the leg and trunk designs of the four- and six-legged walking machines, respectively. <p> Different behavior controls for generating the biologically inspired reactive behaviors are developed on the basis of a modular neural structure. Each behavior control consists of a neural preprocessing module and a neural control module. Preprocessing is for sensory signals while the neural control generates basic locomotion and changes the appropriate motions, e.g. turning left, right or walking backward, with respect to sensory signals. Neural preprocessing and control are formed by realizing discrete-time dynamical properties of recurrent neural networks. Parts of the networks are generated and optimized by using an evolutionary algorithm. Utilizing the modular neural structure, the coupling of the neural control module with different neural preprocessing modules leads to the desired behavior controllers, e.g. obstacle avoidance and sound tropism. Furthermore, these behavior controllers are then fused by using a sensor fusion technique consisting of lookup table and time scheduling methods to obtain an effective behavior fusion controller, whereby different neural preprocessing modules have to cooperate. <p> Eventually, all of these reactive behavior controllers together with the physical sensor systems are implemented on the physical walking machines to be tested in a real world environment. The fully equipped walking machines can be seen as artificial perception-action systems. As a result, the walking machine(s) is able to respond to environmental stimuli, e.g. wandering around, sound tropism (positive tropism), avoiding obstacles and even escaping from corners as well as deadlock situations (negative tropism). The developed controller is universal in the sense that it can be implemented on different types of walking machines, e.g. four- and six-legged walking machines, giving comparably good results without changing parameters.Im Bereich biologisch inspirierter Laufmaschinen konzentrierte sich die Forschung meist auf die reine Bewegungskontrolle sowie das mechanische Design. Obwohl ein Teil dieser Forschung sich auch mit der Erzeugung reaktiver Verhaltensweisen von Robotern beschäftigte, war dies auf einige wenige reaktive Verhaltensweisen beschränkt; und zwar war auf einem Roboter nur jeweils eine Verhaltensweise implementiert. Es gibt nur wenige Ansätze, die sich mit der Erzeugung mehrerer reaktiver Verhaltensweisen einer Maschine gleichzeitig beschäftigen. Im Allgemeinen wurden Laufmaschinen nur zum Zwecke der reinen Fortbewegung konzipiert, d.h. ohne dass sie ihre Umgebung wahrnehmen konnten. <p> Diese Arbeit stellt biologisch inspirierte Laufmaschinen vor, welche mehrere verschiedene reaktive Verhaltensweisen zeigen. Inspiriert vom Hindernisvermeidungs- und Fluchtverhalten der Skorpione und Kakerlaken wird ein solches Verhalten in der Laufmaschine mittels eines negativen Tropismus erzeugt. Andererseits wird ein akustisch motiviertes Verhalten, ein sog. “akustischer Tropismus” (Sound Tropism), in Analogie zum Jagdverhalten von Spinnen, als Beispiel eines positiven Tropismus angewendet. Um die oben beschriebenen Verhalten in abstrahierter Weise reproduzieren zu können, wird außerdem der biologische Wahrnehmungsapparat der genannten Tiere im Hinblick auf ihre prinzipielle Funktionalität untersucht. Zusätzlich werden die Morphologien von Salamander und Kakerlake, welche für effiziente Bewegung gebaut sind, für die Bein- und Körpergestaltung in Betracht gezogen. <p> Basierend auf einem modularen neuronalen Modell werden verschiedene Verhaltenskontroller für die Erzeugung biologisch inspirierter reaktiver Verhaltensweisen entwickelt. Jede Verhaltenskontrolle besteht aus neuronalen Signal-Vorverarbeitungseinheiten und Kontrollmodulen. Für die Vorverarbeitung sensorischer Signale werden rekurrente neuronale Netze genutzt, ebenso wie für die Kontrolle und die Erzeugung von Laufbewegungen, sowie der Änderung der Bewegung, z.B. Drehung nach rechts, links oder rückwärts, in Abhängigkeit von Sensorsignalen. Die effektive neuronale Verarbeitung und Kontrolle wird erreicht durch Ausnutzung der dynamisschen Eigenschaften der rekurrenten neuronalen Netze, die zum Teil durch evolutionäre Algorithmen konstruiert bzw. optimiert wurden. Den modularen Aufbau nutzend führt eine Kombination der verschiedenen neuronalen Verarbeitungseinheiten zu den gewünschten Verhaltenssteuerungen. Des weiteren werden diese Verhaltenssteuerungen zusammengeführt mittels einer Sensor-Fusions-Technik, welche aus Tabellen- und “Time-Scheduling” -Methoden besteht. Damit entsteht letztlich eine neue effektive verhaltenfusionierte Steuerung, die sich auf verschiedenste Laufmaschinen übertragen läßt. <p> Abschließend werden alle diese reaktiven Verhaltenssteuerungen zusammen mit einem Sensorsystem in physikalischen Laufmaschinen implementiert, um sie zu testen und als künstliche Perzeptions-Aktions-Maschine zu demonstrieren. Es wird gezeigt, dass die Laufmaschinen in der Lage sind in der Umgebung umherzuwandern und auf Reize der Umgebung zu reagieren, z.B. durch akustischen Tropismus (positiver Tropismus), durch Hindernisvermeidung und sogar durch Entkommen aus Ecken und Sackgassen (negativer Tropismus). Der entwickelte Kontroller ist universell in dem Sinne, dass er auf Laufmaschinen mit unterschiedlicher Beinanzahl, hier vier und sechs Beine, ohne Parameteranpassung mit vergleichbaren Ergebnissen implentiert werden kann

Online behaviour of luxury brand advocates: differences between active advocates and passive loyalists

The study aims to identify online behaviours of luxury brand advocates referring to differentiation between active and passive loyalists. A netnographic approach was used to observe groups of luxury handbag advocates. Key findings include an identification of engagement manifested in positive word of mouth and enthusiastic brand recommendation. Advocates routinely share their love of particular brands, openly expressing joy and sharing heightened levels of self-esteem. Engaged passive loyalists tend to share less with peers, but instead celebrate their purchases more personally

Design and Development a Novel Web-based GIS for Surveillance and Monitoring of Diarrhea by Using of Free Open Source Software

The prevalence of diarrhea is viewed as a serious problem greatly affecting the society. The plan to prevent and control the spread of diarrhea requires large amounts of data for data processing. Disease prevalence situation is still represented in elusive form. Therefore; to create people understands of diarrhea conditions; a Web-based GIS was developed for surveillance and monitoring of diarrhea in Mahasarakham Province. The main gold of this study was to represent statistical data on diarrhea collected during 2008-2011 by applying Free Open Source Software GIS technology for surveillance and monitoring of diarrhea in Mahasarakham Province. Besides; it aimed to represent novel spatial data and attribute data on diarrhea via internet network; facilitating data view in map form as well as planning surveillance and monitoring of diarrhea with GIS technology. Results found that a novel Web-based GIS user-friendly system for surveillance and monitoring of diarrhea is efficient and practical. People can access data at anytime from anywhere with an internet connection. Keywords: Web-based GIS; Surveillance and monitoring; Diarrhea; Free Open Source Softwar

Multiple chaotic central pattern generators with learning for legged locomotion and malfunction compensation

An originally chaotic system can be controlled into various periodic dynamics. When it is implemented into a legged robot's locomotion control as a central pattern generator (CPG), sophisticated gait patterns arise so that the robot can perform various walking behaviors. However, such a single chaotic CPG controller has difficulties dealing with leg malfunction. Specifically, in the scenarios presented here, its movement permanently deviates from the desired trajectory. To address this problem, we extend the single chaotic CPG to multiple CPGs with learning. The learning mechanism is based on a simulated annealing algorithm. In a normal situation, the CPGs synchronize and their dynamics are identical. With leg malfunction or disability, the CPGs lose synchronization leading to independent dynamics. In this case, the learning mechanism is applied to automatically adjust the remaining legs' oscillation frequencies so that the robot adapts its locomotion to deal with the malfunction. As a consequence, the trajectory produced by the multiple chaotic CPGs resembles the original trajectory far better than the one produced by only a single CPG. The performance of the system is evaluated first in a physical simulation of a quadruped as well as a hexapod robot and finally in a real six-legged walking machine called AMOSII. The experimental results presented here reveal that using multiple CPGs with learning is an effective approach for adaptive locomotion generation where, for instance, different body parts have to perform independent movements for malfunction compensation.Comment: 48 pages, 16 figures, Information Sciences 201

Mini Review: Comparison of Bio-Inspired Adhesive Feet of Climbing Robots on Smooth Vertical Surfaces

Developing climbing robots for smooth vertical surfaces (e.g., glass) is one of the most challenging problems in robotics. Here, the adequate functioning of an adhesive foot is an essential factor for successful locomotion performance. Among the various technologies (such as dry adhesion, wet adhesion, magnetic adhesion, and pneumatic adhesion), bio-inspired dry adhesion has been actively studied and successfully applied to climbing robots. Thus, this review focuses on the characteristics of two different types of foot microstructures, namely spatula-shaped and mushroom-shaped, capable of generating such adhesion. These are the most used types of foot microstructures in climbing robots for smooth vertical surfaces. Moreover, this review shows that the spatula-shaped feet are particularly suitable for massive and one-directional climbing robots, whereas mushroom-shaped feet are primarily suitable for light and all-directional climbing robots. Consequently, this study can guide roboticists in selecting the right adhesive foot to achieve the best climbing ability for future robot developments

Integrated Neural Adaptive Control for In-pipe Robot Locomotion

The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee.Poster Session P2

Can Chaos be utilized as exploration noise for locomotion learning?

The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee.Poster Session P