Design and Programming of 5 Axis Manipulator Robot with GrblGru Open Source Software on Preparing Vocational Students’ Robotic Skills

The rapid development of technology at the end of this decade, the industrial world is changing the human resources they have using the help of robot technology. The use of a robot was chosen because of the accuracy and precision that it can do in doing the job. In addition, robotic technology requires only one programming to do many things. Thus, there are many advantages for companies by using robotic technology in their production processes. This research aims to designing and building arm robot prototype to teach the robotics programming language. The result of this research is an arm robot prototype with Arduino Mega 2560 based programming. In addition, the robot movement programming uses the open source GrblGru software Grbl based. The GrblGru used for interpreting G-code and to convert pulse and direction information to control the stepper motor. This research concludes that there are 5 importance steps on develop the arm robot prototype, 1. Analyze; 2. Design; 3. Develop; 4. Evaluate; and 5. Implementation. With the GrblGru software the movements of arm robot prototype can work on simulation mode and control mode, there for students easier to study robotics programming language

Engineering Self-Adaptive Collective Processes for Cyber-Physical Ecosystems

The pervasiveness of computing and networking is creating significant opportunities for building valuable socio-technical systems. However, the scale, density, heterogeneity, interdependence, and QoS constraints of many target systems pose severe operational and engineering challenges. Beyond individual smart devices, cyber-physical collectives can provide services or solve complex problems by leveraging a “system effect” while coordinating and adapting to context or environment change. Understanding and building systems exhibiting collective intelligence and autonomic capabilities represent a prominent research goal, partly covered, e.g., by the field of collective adaptive systems. Therefore, drawing inspiration from and building on the long-time research activity on coordination, multi-agent systems, autonomic/self-* systems, spatial computing, and especially on the recent aggregate computing paradigm, this thesis investigates concepts, methods, and tools for the engineering of possibly large-scale, heterogeneous ensembles of situated components that should be able to operate, adapt and self-organise in a decentralised fashion. The primary contribution of this thesis consists of four main parts. First, we define and implement an aggregate programming language (ScaFi), internal to the mainstream Scala programming language, for describing collective adaptive behaviour, based on field calculi. Second, we conceive of a “dynamic collective computation” abstraction, also called aggregate process, formalised by an extension to the field calculus, and implemented in ScaFi. Third, we characterise and provide a proof-of-concept implementation of a middleware for aggregate computing that enables the development of aggregate systems according to multiple architectural styles. Fourth, we apply and evaluate aggregate computing techniques to edge computing scenarios, and characterise a design pattern, called Self-organising Coordination Regions (SCR), that supports adjustable, decentralised decision-making and activity in dynamic environments.Con lo sviluppo di informatica e intelligenza artificiale, la diffusione pervasiva di device computazionali e la crescente interconnessione tra elementi fisici e digitali, emergono innumerevoli opportunità per la costruzione di sistemi socio-tecnici di nuova generazione. Tuttavia, l'ingegneria di tali sistemi presenta notevoli sfide, data la loro complessità—si pensi ai livelli, scale, eterogeneità, e interdipendenze coinvolti. Oltre a dispositivi smart individuali, collettivi cyber-fisici possono fornire servizi o risolvere problemi complessi con un “effetto sistema” che emerge dalla coordinazione e l'adattamento di componenti fra loro, l'ambiente e il contesto. Comprendere e costruire sistemi in grado di esibire intelligenza collettiva e capacità autonomiche è un importante problema di ricerca studiato, ad esempio, nel campo dei sistemi collettivi adattativi. Perciò, traendo ispirazione e partendo dall'attività di ricerca su coordinazione, sistemi multiagente e self-*, modelli di computazione spazio-temporali e, specialmente, sul recente paradigma di programmazione aggregata, questa tesi tratta concetti, metodi, e strumenti per l'ingegneria di ensemble di elementi situati eterogenei che devono essere in grado di lavorare, adattarsi, e auto-organizzarsi in modo decentralizzato. Il contributo di questa tesi consiste in quattro parti principali. In primo luogo, viene definito e implementato un linguaggio di programmazione aggregata (ScaFi), interno al linguaggio Scala, per descrivere comportamenti collettivi e adattativi secondo l'approccio dei campi computazionali. In secondo luogo, si propone e caratterizza l'astrazione di processo aggregato per rappresentare computazioni collettive dinamiche concorrenti, formalizzata come estensione al field calculus e implementata in ScaFi. Inoltre, si analizza e implementa un prototipo di middleware per sistemi aggregati, in grado di supportare più stili architetturali. Infine, si applicano e valutano tecniche di programmazione aggregata in scenari di edge computing, e si propone un pattern, Self-Organising Coordination Regions, per supportare, in modo decentralizzato, attività decisionali e di regolazione in ambienti dinamici

Poster Abstract: Towards Spatial Macroprogramming for Sensing and Actuating Robot Swarms

We present our ongoing work on the design of macroprogramming abstractions to program sensing and actuating applications using robot swarms. Robots can sample the environment and act on it where no other sensor can reach, e.g., to monitor the environment at altitude with aerial robots. Programming the individual behavior of multiple coordinating robots is difficult. We design LiftOff, a macroprogramming abstraction that allows to program robot swarms collectively, by creating the illusion of a single computing device that occupies the entire physical space of interest. We achieve this by giving variables and values in a programming language a spatial semantics. In LiftOff, values may be associated to a location, and programmers use the same variable to access different values at different locations, sparing the need to manually create a mapping from variables to spatial values. LiftOff applications execute synchronously or based on lazy evaluation. The former allows precise program analysis, e.g., using model checking, whilst the latter potentially executes faster. In this paper, we report on LiftOff’s initial design and prototypes. Categories and Subject Descriptors [Software and its engineering]: General programming languagesVery high level languages; [Computer systems organization]: Embedded and cyber-physical system