scholarly journals Model Checking Real-Time Properties on the Functional Layer of Autonomous Robots

2016 ◽  
pp. 383-399 ◽  
Author(s):  
Mohammed Foughali ◽  
Bernard Berthomieu ◽  
Silvano Dal Zilio ◽  
Félix Ingrand ◽  
Anthony Mallet
Keyword(s):  
Model Checking ◽  
Real Time ◽  
Autonomous Robots ◽  
Functional Layer

Real time terrain identification of autonomous robots using machine learning

2020 ◽  
Vol 4 (3) ◽  
pp. 265-277
Author(s):  
M. G. Harinarayanan Nampoothiri ◽  
P. S. Godwin Anand ◽  
Rahul Antony
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Autonomous Robots

Schedulability Analysis for Timed Automata With Tasks

2021 ◽  
Vol 20 (5s) ◽  
pp. 1-26
Author(s):  
Jinghao Sun ◽  
Nan Guan ◽  
Rongxiao Shi ◽  
Guozhen Tan ◽  
Wang Yi
Keyword(s):  
Model Checking ◽  
State Space ◽  
Real Time ◽  
Timed Automata ◽  
Schedulability Analysis ◽  
Scheduling Theory ◽  
Real Time Scheduling ◽  
Analysis Techniques ◽  
Model Complex ◽  
Time Scheduling

Research on modeling and analysis of real-time computing systems has been done in two areas, model checking and real-time scheduling theory. In model checking, an expressive modeling formalism such as timed automata (TA) is used to model complex systems, but the analysis is typically very expensive due to state-space explosion. In real-time scheduling theory, the analysis techniques are highly efficient, but the models are often restrictive. In this paper, we aim to exploit the possibility of applying efficient analysis techniques rooted in real-time scheduling theory to analysis of real-time task systems modeled by timed automata with tasks (TAT). More specifically, we develop efficient techniques to analyze the feasibility of TAT-based task models (i.e., whether all tasks can meet their deadlines on single-processor) using demand bound functions (DBF), a widely used workload abstraction in real-time scheduling theory. Our proposed analysis method has a pseudo-polynomial time complexity if the number of clocks used to model each task is bounded by a constant, which is much lower than the exponential complexity of the traditional model-checking based analysis approach (also assuming the number of clocks is bounded by a constant). We apply dynamic programming techniques to implement the DBF-based analysis framework, and propose state space pruning techniques to accelerate the analysis process. Experimental results show that our DBF-based method can analyze a TAT system with 50 tasks within a few minutes, which significantly outperforms the state-of-the-art TAT-based schedulability analysis tool TIMES.

scholarly journals Symbolic Model Checking for Real-Time Systems

1994 ◽  
Vol 111 (2) ◽  
pp. 193-244 ◽  
Author(s):  
T.A. Henzinger ◽  
X. Nicollin ◽  
J. Sifakis ◽  
S. Yovine
Keyword(s):  
Model Checking ◽  
Real Time ◽  
Symbolic Model Checking ◽  
Real Time Systems ◽  
Symbolic Model ◽  
Time Systems

Modeling and analyzing real-time wireless sensor and actuator networks using actors and model checking

2017 ◽  
Vol 20 (5) ◽  
pp. 547-561 ◽  
Author(s):  
Ehsan Khamespanah ◽  
Marjan Sirjani ◽  
Kirill Mechitov ◽  
Gul Agha
Keyword(s):  
Model Checking ◽  
Real Time ◽  
Wireless Sensor

scholarly journals Autonomous and Safe Navigation of Mobile Robots in Vineyard with Smooth Collision Avoidance

Agriculture ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 954
Author(s):  
Abhijeet Ravankar ◽  
Ankit A. Ravankar ◽  
Arpit Rawankar ◽  
Yohei Hoshino
Keyword(s):  
Mobile Robots ◽  
Real Time ◽  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Autonomous Robots ◽  
Robot Navigation ◽  
Indoor Environments ◽  
Safe Distance ◽  
Field Robots ◽  
Safe Navigation

In recent years, autonomous robots have extensively been used to automate several vineyard tasks. Autonomous navigation is an indispensable component of such field robots. Autonomous and safe navigation has been well studied in indoor environments and many algorithms have been proposed. However, unlike structured indoor environments, vineyards pose special challenges for robot navigation. Particularly, safe robot navigation is crucial to avoid damaging the grapes. In this regard, we propose an algorithm that enables autonomous and safe robot navigation in vineyards. The proposed algorithm relies on data from a Lidar sensor and does not require a GPS. In addition, the proposed algorithm can avoid dynamic obstacles in the vineyard while smoothing the robot’s trajectories. The curvature of the trajectories can be controlled, keeping a safe distance from both the crop and the dynamic obstacles. We have tested the algorithm in both a simulation and with robots in an actual vineyard. The results show that the robot can safely navigate the lanes of the vineyard and smoothly avoid dynamic obstacles such as moving people without abruptly stopping or executing sharp turns. The algorithm performs in real-time and can easily be integrated into robots deployed in vineyards.

Empirical analysis of cyber-attacks to an indoor real time localization system for autonomous robots

2017 ◽  
Vol 70 ◽  
pp. 422-435 ◽  
Author(s):  
Ángel Manuel Guerrero-Higueras ◽  
Noemí DeCastro-García ◽  
Francisco Javier Rodríguez-Lera ◽  
Vicente Matellán
Keyword(s):  
Real Time ◽  
Empirical Analysis ◽  
Autonomous Robots ◽  
Cyber Attacks ◽  
Localization System

KRONOS — Model Checking of Real-time Systems

2001 ◽  
pp. 161-168
Author(s):  
Béatrice Bérard ◽  
Michel Bidoit ◽  
Alain Finkel ◽  
François Laroussinie ◽  
Antoine Petit ◽  
...  
Keyword(s):  
Model Checking ◽  
Real Time ◽  
Real Time Systems ◽  
Time Systems
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