scholarly journals Fault-Tolerant Multi-Robot Operational Strategy for Material Transport Systems Considering Maintenance Activity

2010 ◽  
Vol 22 (4) ◽  
pp. 485-495 ◽  
Author(s):  
Satoshi Hoshino ◽  
◽  
Hiroya Seki ◽  
Yuji Naka ◽  
Jun Ota ◽  
...  
Keyword(s):  
Fault Tolerant ◽  
Industrial Applications ◽  
Transport Systems ◽  
Reliability Engineering ◽  
Material Transport ◽  
Corrective Maintenance ◽  
Operational Strategies ◽  
Maintenance Activity ◽  
Robot Systems ◽  
Multi Robot

In automated robotic systems, a robot undergoing corrective maintenance (i.e., repair) or preventive maintenance (i.e., inspection) may become a disturbance of operations for other working robots. Therefore, maintenance of a robot has to be performed adequately. Multi-robot systems have the capability for the substitution and complement of such a robot. To introduce the multi-robot technology in industrial applications, we propose fault-tolerant multi-robot operational strategies for a material transport system focusing on the robot behavior. Working robots, while switching between normal and fault-tolerant operational strategies reactively according to the presence or absence of a robot undergoing maintenance, accomplish tasks. Through simulation experiments, the effectiveness of the proposed strategies is discussed. In addition, an integrated strategy for some failure rates of the robot is investigated. Finally, a maintenance activity for the robots is modeled on the basis of reliability engineering and the reasonability of preventive and corrective maintenance is discussed.

scholarly journals Swarm SLAM: Challenges and Perspectives

2021 ◽  
Vol 8 ◽  
Author(s):  
Miquel Kegeleirs ◽  
Giorgio Grisetti ◽  
Mauro Birattari
Keyword(s):  
Fault Tolerant ◽  
Point Of View ◽  
Decentralized System ◽  
Robot Swarm ◽  
Cost Constraints ◽  
Localization And Mapping ◽  
Robot Systems ◽  
The Moment ◽  
Hostile Environments ◽  
Multi Robot

A robot swarm is a decentralized system characterized by locality of sensing and communication, self-organization, and redundancy. These characteristics allow robot swarms to achieve scalability, flexibility and fault tolerance, properties that are especially valuable in the context of simultaneous localization and mapping (SLAM), specifically in unknown environments that evolve over time. So far, research in SLAM has mainly focused on single- and centralized multi-robot systems—i.e., non-swarm systems. While these systems can produce accurate maps, they are typically not scalable, cannot easily adapt to unexpected changes in the environment, and are prone to failure in hostile environments. Swarm SLAM is a promising approach to SLAM as it could leverage the decentralized nature of a robot swarm and achieve scalable, flexible and fault-tolerant exploration and mapping. However, at the moment of writing, swarm SLAM is a rather novel idea and the field lacks definitions, frameworks, and results. In this work, we present the concept of swarm SLAM and its constraints, both from a technical and an economical point of view. In particular, we highlight the main challenges of swarm SLAM for gathering, sharing, and retrieving information. We also discuss the strengths and weaknesses of this approach against traditional multi-robot SLAM. We believe that swarm SLAM will be particularly useful to produce abstract maps such as topological or simple semantic maps and to operate under time or cost constraints.

A decentralized fault tolerant control strategy for multi-robot systems

2014 ◽  
Vol 47 (3) ◽  
pp. 6642-6647 ◽  
Author(s):  
Filippo Arrichiello ◽  
Alessandro Marino ◽  
Francesco Pierri
Keyword(s):  
Control Strategy ◽  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Robot Systems ◽  
Multi Robot

scholarly journals Scalable time-constrained planning of multi-robot systems

2020 ◽  
Vol 44 (8) ◽  
pp. 1451-1467
Author(s):  
Alexandros Nikou ◽  
Shahab Heshmati-alamdari ◽  
Dimos V. Dimarogonas
Keyword(s):  
Real Life ◽  
Industrial Applications ◽  
Control Input ◽  
Time Duration ◽  
Control Laws ◽  
Robot Systems ◽  
Limited Sensing ◽  
The Individual ◽  
High Level ◽  
Multi Robot

Abstract This paper presents a scalable procedure for time-constrained planning of a class of uncertain nonlinear multi-robot systems. In particular, we consider N robotic agents operating in a workspace which contains regions of interest (RoI), in which atomic propositions for each robot are assigned. The main goal is to design decentralized and robust control laws so that each robot meets an individual high-level specification given as a metric interval temporal logic (MITL), while using only local information based on a limited sensing radius. Furthermore, the robots need to fulfill certain desired transient constraints such as collision avoidance between them. The controllers, which guarantee the transition between regions, consist of two terms: a nominal control input, which is computed online and is the solution of a decentralized finite-horizon optimal control problem (DFHOCP); and an additive state feedback law which is computed offline and guarantees that the real trajectories of the system will belong to a hyper-tube centered along the nominal trajectory. The controllers serve as actions for the individual weighted transition system (WTS) of each robot, and the time duration required for the transition between regions is modeled by a weight. The DFHOCP is solved at every sampling time by each robot and then necessary information is exchanged between neighboring robots. The proposed approach is scalable since it does not require a product computation among the WTS of the robots. The proposed framework is experimentally tested and the results show that the proposed framework is promising for solving real-life robotic as well as industrial applications.

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