Run-Time Compositional Software Platform for Autonomous NXT Robots

2019 ◽  
pp. 649-662
Author(s):  
Ning Gui ◽  
Vincenzo De Florio ◽  
Chris Blondia
Keyword(s):  
Autonomous Robots ◽  
Software Systems ◽  
Robot System ◽  
Unstructured Environments ◽  
System A ◽  
Adaptive Middleware ◽  
Context Knowledge ◽  
Run Time ◽  
Compositional Software ◽  
Robotic Applications

Autonomous Robots normally perform tasks in unstructured environments, with little or no continuous human guidance. This calls for context-aware, self-adaptive software systems. This paper aims at providing a flexible adaptive middleware platform to seamlessly integrate multiple adaptation logics during the run-time. To support such an approach, a reconfigurable middleware system “ACCADA” was designed to provide compositional adaptation. During the run-time, context knowledge is used to select the most appropriate adaptation modules so as to compose an adaptive system best-matching the current exogenous and endogenous conditions. Together with a structure modeler, this allows robotic applications' structure to be autonomously (re)-constructed and (re)-configured. This paper applies this model on a Lego NXT robot system. A remote NXT model is designed to wrap and expose native NXT devices into service components that can be managed during the run-time. A dynamic UI is implemented which can be changed and customized according to system conditions. Results show that the framework changes robot adaptation behavior during the run-time.

Run-Time Compositional Software Platform for Autonomous NXT Robots

2012 ◽  
pp. 137-149
Author(s):  
Ning Gui ◽  
Vincenzo De Florio ◽  
Chris Blondia
Keyword(s):  
Autonomous Robots ◽  
Software Systems ◽  
Robot System ◽  
Unstructured Environments ◽  
System A ◽  
Adaptive Middleware ◽  
Context Knowledge ◽  
Run Time ◽  
Compositional Software ◽  
Robotic Applications

Autonomous Robots normally perform tasks in unstructured environments, with little or no continuous human guidance. This calls for context-aware, self-adaptive software systems. This paper aims at providing a flexible adaptive middleware platform to seamlessly integrate multiple adaptation logics during the run-time. To support such an approach, a reconfigurable middleware system “ACCADA” was designed to provide compositional adaptation. During the run-time, context knowledge is used to select the most appropriate adaptation modules so as to compose an adaptive system best-matching the current exogenous and endogenous conditions. Together with a structure modeler, this allows robotic applications’ structure to be autonomously (re)-constructed and (re)-configured. This paper applies this model on a Lego NXT robot system. A remote NXT model is designed to wrap and expose native NXT devices into service components that can be managed during the run-time. A dynamic UI is implemented which can be changed and customized according to system conditions. Results show that the framework changes robot adaptation behavior during the run-time.

Run-Time Compositional Software Platform for Autonomous NXT Robots

2011 ◽  
Vol 2 (2) ◽  
pp. 37-50 ◽  
Author(s):  
Ning Gui ◽  
Vincenzo De Florio ◽  
Chris Blondia
Keyword(s):  
Autonomous Robots ◽  
Software Systems ◽  
Context Aware ◽  
Robot System ◽  
System A ◽  
Adaptive Middleware ◽  
Context Knowledge ◽  
Run Time ◽  
Compositional Software ◽  
Robotic Applications

Autonomous Robots normally perform tasks in unstructured environments, with little or no continuous human guidance. This calls for context-aware, self-adaptive software systems. This paper aims at providing a flexible adaptive middleware platform to seamlessly integrate multiple adaptation logics during the run-time. To support such an approach, a reconfigurable middleware system “ACCADA” was designed to provide compositional adaptation. During the run-time, context knowledge is used to select the most appropriate adaptation modules so as to compose an adaptive system best-matching the current exogenous and endogenous conditions. Together with a structure modeler, this allows robotic applications’ structure to be autonomously (re)-constructed and (re)-configured. This paper applies this model on a Lego NXT robot system. A remote NXT model is designed to wrap and expose native NXT devices into service components that can be managed during the run-time. A dynamic UI is implemented which can be changed and customized according to system conditions. Results show that the framework changes robot adaptation behavior during the run-time.

scholarly journals Verification of visibility-based properties on multiple moving robots in an environment with obstacles

2018 ◽  
Vol 15 (4) ◽  
pp. 172988141878665 ◽  
Author(s):  
Ali Narenji Sheshkalani ◽  
Ramtin Khosravi
Keyword(s):  
State Space ◽  
Autonomous Robots ◽  
The State ◽  
Robot System ◽  
Discrete State ◽  
Verification Method ◽  
Distributed Processes ◽  
Analytical Proof ◽  
Motion Strategy ◽  
Multi Robot

A multi-robot system consists of a number of autonomous robots moving within an environment to achieve a common goal. Each robot decides to move based on information obtained from various sensors and gathered data received through communicating with other robots. In order to prove the system satisfies certain properties, one can provide an analytical proof or use a verification method. This article presents a new notion to prove visibility-related properties of a multi-robot system by introducing an automated verification method. Precisely, we propose a method to automatically generate a discrete state space of a given multi-robot system and verify the correctness of the desired properties by means of model-checking tools and algorithms. We construct the state space of a number of robots, each moves freely inside a bounded polygonal area with obstacles. The generated state space is then used to verify visibility properties (e.g. if the communication graph of robots is connected) by means of the construction and analysis of distributed processes model checker. Using our method, there is no need to analytically prove that the properties are preserved with every change in the motion strategy of the robots. We have implemented a tool to automatically generate the state space and verified some properties to demonstrate the applicability of our method in various environments.

An Ontology-Driven System for E-Learning and Knowledge Management

2010 ◽  
pp. 302-324 ◽  
Author(s):  
Gilbert Paquette
Keyword(s):  
Knowledge Management ◽  
Research Network ◽  
Software Systems ◽  
Operation System ◽  
Ontological Engineering ◽  
Modeling Tool ◽  
Graphic Model ◽  
Driven System ◽  
E Learning ◽  
Run Time

Between 2003 and 2008, within the LORNET research network (www.lornet.org), our team has been designing and developing TELOS, an innovative operation system for eLearning and knowledge management environments that is driven by a technical ontology. After presenting the underlying principles of this system, we will develop a graphic model of the resulting ontology that captures the conceptual architecture of the system. Next, we will present the main aggregation modeling tool and the way it is related to the TELOS Ontology. Finally, we will illustrate how the ontology is used to drive the system at run-time. The conclusion will discuss the contri- bution of this research to the field of ontological engineering of software systems.

scholarly journals Localization in Unstructured Environments: Towards Autonomous Robots in Forests with Delaunay Triangulation

2020 ◽  
Vol 12 (11) ◽  
pp. 1870 ◽  
Author(s):  
Qingqing Li ◽  
Paavo Nevalainen ◽  
Jorge Peña Queralta ◽  
Jukka Heikkonen ◽  
Tomi Westerlund
Keyword(s):  
Autonomous Robots ◽  
Laser Scanner ◽  
Point Clouds ◽  
Time Data ◽  
Unstructured Environments ◽  
Accurate Localization ◽  
Novel Approach ◽  
Local Point ◽  
Feature Based ◽  
Real Time Data Processing

Autonomous harvesting and transportation is a long-term goal of the forest industry. One of the main challenges is the accurate localization of both vehicles and trees in a forest. Forests are unstructured environments where it is difficult to find a group of significant landmarks for current fast feature-based place recognition algorithms. This paper proposes a novel approach where local point clouds are matched to a global tree map using the Delaunay triangularization as the representation format. Instead of point cloud based matching methods, we utilize a topology-based method. First, tree trunk positions are registered at a prior run done by a forest harvester. Second, the resulting map is Delaunay triangularized. Third, a local submap of the autonomous robot is registered, triangularized and matched using triangular similarity maximization to estimate the position of the robot. We test our method on a dataset accumulated from a forestry site at Lieksa, Finland. A total length of 200 m of harvester path was recorded by an industrial harvester with a 3D laser scanner and a geolocation unit fixed to the frame. Our experiments show a 12 cm s.t.d. in the location accuracy and with real-time data processing for speeds not exceeding 0.5 m/s. The accuracy and speed limit are realistic during forest operations.

Dynamic model based formation control and obstacle avoidance of multi-robot systems

Robotica ◽  
2008 ◽  
Vol 26 (3) ◽  
pp. 345-356 ◽  
Author(s):  
Celso De La Cruz ◽  
Ricardo Carelli
Keyword(s):  
Dynamic Model ◽  
Obstacle Avoidance ◽  
Formation Control ◽  
Inverse Dynamics ◽  
Single Equation ◽  
Model Parameters ◽  
Robot System ◽  
System A ◽  
Robot Systems ◽  
Multi Robot

SUMMARYThis work presents, first, a complete dynamic model of a unicycle-like mobile robot that takes part in a multi-robot formation. A linear parameterization of this model is performed in order to identify the model parameters. Then, the robot model is input-output feedback linearized. On a second stage, for the multi-robot system, a model is obtained by arranging into a single equation all the feedback linearized robot models. This multi-robot model is expressed in terms of formation states by applying a coordinate transformation. The inverse dynamics technique is then applied to design a formation control. The controller can be applied both to positioning and to tracking desired robot formations. The formation control can be centralized or decentralized and scalable to any number of robots. A strategy for rigid formation obstacle avoidance is also proposed. Experimental results validate the control system design.

Dynamic Service Identification in A Distributed Environment

1999 ◽  
Vol 3 (5) ◽  
pp. 401-408 ◽  
Author(s):  
E.Damiani ◽  
◽  
M.G.Fugini ◽  
Keyword(s):  
Data Model ◽  
Fuzzy Data ◽  
Query Execution ◽  
Functional Information ◽  
Distributed Environment ◽  
System A ◽  
Service Identification ◽  
Fuzzy Query ◽  
Run Time

Dynamic invocation of services in O-O execution environments requires identification of server objects which are "fit" to a certain task on the basis of available functional and non-functional information. CORBA-compliant environments store such information in a Trader system which can be browsed or queried by client objects. In this paper a fuzzy data model is proposed as the basis of the design of a Trader system. A fuzzy query algebra is described allowing for deriving operator definitions (and, therefore, query execution mechanisms) at run time, on the basis of user-selected semantics.

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