This paper presents a tool for automatic generation of ANSI C code from models expressed in IOPT (Input-Output Place-Transition) Petri Nets. The inputs of the tool are PNML (Petri Nets Mark-up Language) files containing the IOPT Petri net models. The tool has two different interfaces: one relying on a simple graphical interface (amenable to be used by humans), and a second one with a command line interface (amenable to be used by humans as well as by other computational systems supporting tools interaction). The tool also allows the user to tune some parts of the automatically generated code considering some characteristics of the implementation platform improving the performance of the generated code. Generated code can be directly deployed into specific controllers; PIC low-cost microcontrollers as well as general purpose PCs have been used for validation.

The ability to precisely classify different types of terrain is extremely important for Unmanned Aerial Vehicles (UAVs). There are multiple situations in which terrain classification is fundamental for achieving a UAV’s mission success, such as emergency landing, aerial mapping, decision making, and cooperation between UAVs in autonomous navigation. Previous research works describe different terrain classification approaches mainly using static features from RGB images taken onboard UAVs. In these works, the terrain is classified from each image taken as a whole, not divided into blocks; this approach has an obvious drawback when applied to images with multiple terrain types. This paper proposes a robust computer vision system to classify terrain types using three main algorithms, which extract features from UAV’s downwash effect: Static textures- Gray-Level Co-Occurrence Matrix (GLCM), Gray-Level Run Length Matrix (GLRLM) and Dynamic textures- Optical Flow method. This system has been fully implemented using the OpenCV library, and the GLCM algorithm has also been partially specified in a Hardware Description Language (VHDL) and implemented in a Field Programmable Gate Array (FPGA)-based platform. In addition to these feature extraction algorithms, a neural network was designed with the aim of classifying the terrain into one of four classes. Lastly, in order to store and access all the classified terrain information, a dynamic map, with this information was generated. The system was validated using videos acquired onboard a UAV with an RGB camera.

This paper presents the IOPT2SS tool, used to automatically generate state-space graphs associated with IOPT (Input-Output Place-Transition) Petri nets models. The new tool accounts with the non autonomous nature of the IOPT Petri net class, where transition firing is constrained by external input events and input signals (expressed in transition guards); on the other hand, transitions can trigger the occurrence of output signal events and place marking can activate output signals. To achieve the performance level necessary for the fast generation of complex state-spaces during reasonable time, the tool employs a compilation strategy, starting with the automatic creation of an optimized C program. When executed, the program will create an hierarchical XML file containing the state-space graph. The output XML file can subsequently be used for model checking and property analysis, applying standard XML query languages. Finally, the output file can be converted to SVG (Scalable Vector Graphics), enabling the graphical visualization of small to medium size state-space graphs. The new tool was implemented using a set of XSL transformations and can be used as a standalone tool or as a building block in higher level frameworks, with easy integration in Web applications and graphical integrated development environments.

This work presents a tool for automatic generation of controllers' implementation code from Petri nets models amenable to be deployed into common platforms using widely used high level programming languages, such as C, C++, and Java. The generated code is linked with platform specific functions, supporting different types of implementation platforms, ranging from low-cost microcontrollers to workstations, and including microcontroller IPs (Intellectual Property) to be embedded into FPGAs (Field Programmable Gate Arrays). The system controller behavior is modeled using IOPT (Input-Output Place-Transition) Petri Nets models, which are represented through PNML (Petri nets Mark-up Language) notation. A tool for automatic code generation was developed, which achieved this goal in cooperation with other developed tools within a model-based development framework. Application to an automation system composed by a set of distributed controllers is presented.

This paper presents an algorithm to efficiently generate the state-space of systems specified using the IOPT Petri-net modeling formalism. IOPT nets are a non-autonomous Petri-net class, based on Place-Transition nets with an extended set of features designed to allow the rapid prototyping and synthesis of system controllers through an existing hardware-software co-design framework. To obtain coherent and deterministic operation, IOPT nets use a maximal-step execution semantics where, in a single execution step, all enabled transitions will fire simultaneously. This fact increases the resulting state-space complexity and can cause an arc “explosion” effect. Real-world applications, with several million states, will reach a higher order of magnitude number of arcs, leading to the need for high performance state-space generator algorithms. The proposed algorithm applies a compilation approach to read a PNML file containing one IOPT model and automatically generate an optimized C program to calculate the corresponding state-space.