Mission Design of a Team of Service Robots

2015 ◽  
pp. 728-749
Author(s):  
Elias K. Xidias ◽  
Nikos A. Aspragathos ◽  
Philip N. Azariadis
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Integrated Approach ◽  
Mission Design ◽  
Service Robots ◽  
Indoor Environments ◽  
Mathematical Entity ◽  
Modified Genetic Algorithm ◽  
Service Stations

The purpose of this chapter is to present an integrated approach for Mission Design of a team of Service Robots that is operating in partially known indoor environments such as libraries, hospitals, or warehouses. The robots are requested to serve a number of service stations while taking into account movement safety and other kinematical constraints. The Bump-Surface concept is used to represent the robots' environment through a single mathematical entity and an optimization problem is formulated representing an aggregation of paths length and movement constraints. Then a modified Genetic Algorithm with parallel populations is used for solving the problem of mission design of a team of service robots on the constructed Bump-Surface. Three simulation examples are presented to show the effectiveness of the presented approach.

scholarly journals Truss’ topology and shape optimization by genetic algorithms

2021 ◽  
Vol 47 ◽  
Author(s):  
Dmitrij Šešok ◽  
Paulius Ragauskas
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Shape Optimization ◽  
Optimization Problem ◽  
Numerical Solutions ◽  
Search Algorithm ◽  
Truss Topology ◽  
Modified Genetic Algorithm ◽  
Topology And Shape Optimization ◽  
System Characteristics

In the paper the global optimization problem of truss systems is studied.  The genetic algorithms are employed for the optimization. As the objective function the structure mass is treated; the constraints include equilibrium, local stability and other requirements.  All the truss system characteristics needed for genetic algorithm are obtained via finite element solution. Topology optimization of truss system is performed using original modified genetic algorithm, while the shape optimization – using ordinary genetic algorithm. Numerical solutions are presented. The obtained solutions are compared with global extremes obtained using full search algorithm.  All the numerical examples are solved using original software.

scholarly journals The Multiagent Planning Problem

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Tamás Kalmár-Nagy ◽  
Giovanni Giardini ◽  
Bendegúz Dezső Bak
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Problem Solver ◽  
Planning Problem ◽  
Genetic Operators ◽  
Total Distance ◽  
Modified Genetic Algorithm ◽  
Multiagent Planning ◽  
Simple Paths ◽  
Better Than

The classical Multiple Traveling Salesmen Problem is a well-studied optimization problem. Given a set ofngoals/targets andmagents, the objective is to findmround trips, such that each target is visited only once and by only one agent, and the total distance of these round trips is minimal. In this paper we describe the Multiagent Planning Problem, a variant of the classical Multiple Traveling Salesmen Problem: given a set ofngoals/targets and a team ofmagents,msubtours (simple paths) are sought such that each target is visited only once and by only one agent. We optimize for minimum time rather than minimum total distance; therefore the objective is to find the Team Plan in which the longest subtour is as short as possible (a min–max problem). We propose an easy to implement Genetic Algorithm Inspired Descent (GAID) method which evolves a set of subtours using genetic operators. We benchmarked GAID against other evolutionary algorithms and heuristics. GAID outperformed the Ant Colony Optimization and the Modified Genetic Algorithm. Even though the heuristics specifically developed for Multiple Traveling Salesmen Problem (e.g.,k-split, bisection) outperformed GAID, these methods cannot solve the Multiagent Planning Problem. GAID proved to be much better than an open-source Matlab Multiple Traveling Salesmen Problem solver.

scholarly journals Mission Planning of Mobile Robots and Manipulators for Service Applications

Robotics ◽  
2013 ◽  
pp. 225-247
Author(s):  
Elias K. Xidias ◽  
Nikos A. Aspragathos ◽  
Philip N. Azariadis
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Mission Planning ◽  
Service Robots ◽  
Service Robot ◽  
Indoor Environments ◽  
Mathematical Entity ◽  
Planning And Scheduling ◽  
Body Of Knowledge ◽  
Planning Approach

The purpose of this chapter is to present a mission planning approach for a service robot, which is moving and manipulating objects in semi-structured and partly known indoor environments such as stores, hospitals, and libraries. The recent advances and trends in motion planning and scheduling of mobile robots carrying manipulators are presented. This chapter adds to the existing body of knowledge of motion planning for Service Robots (SRs), an approach that is based on the Bump-Surface concept. The Bump-Surface concept is used to represent the entire robot’s environment through a single mathematical entity. Criteria and constraints for the mission planning are adapted to the service robots. Simulation examples are presented to show the effectiveness of the presented approach.

Mission Planning of Mobile Robots and Manipulators for Service Applications

2012 ◽  
pp. 51-77 ◽  
Author(s):  
Elias K. Xidias ◽  
Nikos A. Aspragathos ◽  
Philip N. Azariadis
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Mission Planning ◽  
Service Robots ◽  
Service Robot ◽  
Indoor Environments ◽  
Mathematical Entity ◽  
Planning And Scheduling ◽  
Body Of Knowledge ◽  
Planning Approach

The purpose of this chapter is to present a mission planning approach for a service robot, which is moving and manipulating objects in semi-structured and partly known indoor environments such as stores, hospitals, and libraries. The recent advances and trends in motion planning and scheduling of mobile robots carrying manipulators are presented. This chapter adds to the existing body of knowledge of motion planning for Service Robots (SRs), an approach that is based on the Bump-Surface concept. The Bump-Surface concept is used to represent the entire robot’s environment through a single mathematical entity. Criteria and constraints for the mission planning are adapted to the service robots. Simulation examples are presented to show the effectiveness of the presented approach.

Mission Design of Mobile Manipulators in Cluttered Environments for Service Applications

2016 ◽  
Vol 4 (1) ◽  
pp. 1-18
Author(s):  
Elias K. Xidias ◽  
Philip N. Azariadis ◽  
Nikos A. Aspragathos
Keyword(s):  
Inverse Image ◽  
Mission Design ◽  
Mobile Manipulator ◽  
Indoor Environments ◽  
Mobile Manipulators ◽  
Mathematical Entity ◽  
End Effector ◽  
Cluttered Environments ◽  
Cost Simulation ◽  
The Given

The purpose of this paper is to present a mission design approach for a service mobile manipulator which is moving and manipulating objects in partly known indoor environments. The mobile manipulator is requested to pick up and place objects on predefined places (stations). The proposed approach is based on the Bump-Surface concept to represent robot's environment through a single mathematical entity. The solution of the mission design problem is searched on a higher dimension Bump-Surface in such a way that its inverse image into the actual robot environment satisfies the given objectives and constraints. The problem's objectives consist of determining the best feasible paths for both the mobile platform and for the manipulator's end-effector so that all the stations are served at the lowest possible cost. Simulation examples are presented to show the effectiveness of the presented approach.

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