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The Braitenberg vehicles and the line following algorithms (Chap. 3) demonstrate reactive behavior, where the action of the robot depends on the current values returned by robot's sensors, not on events that happened previously. In Sect. 4.1 we present the concept of state and finite state machines (FSM). Sections 4.2 and 4.3 show how certain Braitenberg vehicles can be implemented with FSMs. Section 4.4 discusses the implementation of FSMs using state variables. 4.1 State Machines The concept of state is very familiar. Consider a toaster: initially, the toaster is in the off state; when you push the lever down, a transition is made to the on state and the heating elements are turned on; finally, when the timer expires, a transition is made back to the off state and the heating elements are turned off. A finite state machine (FSM) 1 consists of a set of states s i and a set of transitions between pairs of states s i , s j. A transition is labeled condition/action: a condition that causes the transition to be taken and an action that is performed when the transition is taken. FSMs can be displayed in state diagrams: off on lever down turn heat on timer expired turn heat off off = toaster off on = toaster on A state is denoted by a circle labeled with the name of the state. States are given short names to save space and their full names are given in a box next to the state 1 Finite state machines are also called finite automata.
Automatika ‒ Journal for Control, Measurement, Electronics, Computing and Communications, 2013
Original scientific paper This paper describes design using state-transition methodology. This state-transition methodology is straightforward, with a simply-perceived relation between the programming and the corresponding sequential function. The current operational function of the system is described as the current state of the system using state-transition programming. The state transition diagram or table describes the current state and the conditions for transition. The operation is transferred to a corresponding destination state when a set of conditions become valid for leaving the current state. Thus, the sequential operation is explicit, and any continuous conditions scanning (from command source and sensors) only include those that are pertinent for leaving the current state. The methodology is highly-structured and efficient, the programming tasks are readily comprehensible, and fault diagnostics can be easily included within the program's structure. The presented application of an automatic sliding-door illustrates the feasibility of this approach. This paper presents the MFSM (Modular Finite-State Machine), the ECA (Event-Condition-Action) system, motion generation, motion control with load estimation, and an example of a DSP (Digital Signal Processor) system. The limitations and attributes of each technique are discussed, and a state-table format is presented with the capability of representing parallel asynchronous sequential processes.
This chapter introduces finite-state machines, a primitive, but useful computational model for both hardware and certain types of software. We also discuss regular expressions, the correspondence between non-deterministic and deterministic machines, and more on grammars. Finally, we describe typical hardware components that are essentially physical realizations of finite-state machines.
2010
State Machines are the basic mechanism used to specify the behaviour of objects in UML based object models and admit the possibility of direct animation or execution of a model. Tools that exploit this potential offer the promise of both supporting early validation of a model under development and allowing generation of final code directly from the model. Recently, we have made some new proposals on how state machines are used to model behaviour: firstly, that complex object behaviour can be best modelled by the parallel composition of multiple state machines; and secondly, that a formal distinction can be made between purely event driven machines and those whose states are derived from other information in the model. We illustrate the advantages of this approach with a small example that shows how it can help reduce redundancy and promote simplicity.
Distributed Autonomous Robotic Systems
Controllers for autonomous robotic systems can be specified using state machines. However, these are typically developed in an ad hoc manner without formal semantics, which makes it difficult to analyse the controller. Simulations are often used during the development, but a rigorous connection between the designed controller and the implementation is often overlooked. This paper presents a statemachine based notation, RoboChart, together with a tool to automatically create code from the state machines, establishing a rigorous connection between specification and implementation. In RoboChart, a robot's controller is specified either graphically or using a textual description language. The controller code for simulation is automatically generated through a direct mapping from the specification. We demonstrate our approach using two case studies (self-organized aggregation and swarm taxis) in swarm robotics. The simulations are presented using two different simulators showing the general applicability of our approach.
Advances in Artificial Life, ECAL 2013, 2013
We propose an approach to the automatic synthesis of robot control software based on the finite state machine (FSM) formalism. In our previous research, we have introduced Boolean network robotics as a novel approach to the automatic design of robot control software. In this paper, we show that it is possible to leverage automatically designed Boolean networks to synthesize FSMs for robot control. Boolean network robotics exhibits a number of interesting properties. Firstly, notwithstanding the large size of the state space of a Boolean network and its ability to display complex and rich dynamics, the automatic design is able to produce networks whose trajectories are confined in small volumes of the state space. Secondly, the automatic design produces networks in which one can identify clusters of states associated with functional behavioral units of the robots. It is our contention that the automatic design of a Boolean network controller can be a convenient intermediate step in the synthesis of a FSM, which offers the advantage of being a compact, readable, and modifiable representation. In this paper, we show that clusters of states traversed by network trajectories can be mapped to states of a FSM. We illustrate the viability of our proposal in two notable robotic tasks, namely collision avoidance and sequence recognition. The first task can be achieved by a memoryless control program, whilst in the second the robots need memory.
Journal of Computing and Information Technology
As an inspiration for robot behavior, it is possible to make analogies between behavior of biological organisms and robot models. Inspired by the behavior of the beetles, we designed reactive, sensor-based behavior for mobile robot. The focus is on intelligent control algorithm, which approximates the behavior of the dor beetle with a Finite State Machine-based Design method. This finite state machine–based approach could be usefull as methodologie for the improved planning of the real-time complex tasks in robot-based manufactoring systems, using information from factory sensor networks, and taking into account the constraints from factory environments. In this paper, we will present the motor control results obtained through experiments, which confirm the effectiveness of the control based on behavior algorithm of living organisms.
International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022
A finite-state machine (FSM) is a computational mathematical model. For design and analysis, circuits and system operations can be represented in a variety of ways. FSM is one of the methods for using a drawing to represent the operations of many circuits and systems in electronic engineering, computer engineering, and so on. In terms of design, the finite state machine is a very simple machine. It is made up of a set of input symbols, output symbols, and states that must be designed. Furthermore, a function of input and output symbols with the current state to give the next state must be present. To simulate the Finite State machine, a software simulator is implemented in this paper using the Visual Basic programming language (in terms of design and operation).Several general examples are represented in this model. However, the software can be used to teach students about FSM and how it works. I.
In the past few decades formal methods were widely studied and used in verification of logic systems especially for design of computer programs in safety-critical areas. This thesis focuses on the control and verification of discrete event systems (DES) by using variable-based approach. We will try to merge the gap between supervisory control theory (SCT) and our variable-based model, and translate the model to computer programs. In particular we will use variables and predicates to realize the supervisor in SCT theory. With the variables and predicates the new model functions like extended finite state machines (EFSM), which is more practical in the engineering field, especially in design of computer programs.
Lecture Notes in Computer Science, 2008
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2003
We introduce a logic for sequential, non distributed Abstract State Machines. Unlike other logics for ASMs which are based on dynamic logic, our logic is based on atomic propositions for the function updates of transition rules. We do not assume that the transition rules of ASMs are in normal form, for example, that they concern distinct cases. Instead we allow structuring concepts of ASM rules including sequential composition and possibly recursive submachine calls. We show that several axioms that have been proposed for reasoning about ASMs are derivable in our system and that the logic is complete for hierarchical (non-recursive) ASMs.
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