scholarly journals Reachability and Coverage Planning for Connected Agents

2019 ◽  
Author(s):  
Tristan Charrier ◽  
Arthur Queffelec ◽  
Ocan Sankur ◽  
François Schwarzentruber
Keyword(s):  
Path Planning ◽  
Information Gathering ◽  
Efficient Algorithms ◽  
Topological Graph ◽  
Topological Graphs ◽  
New Class ◽  
Multi Agent ◽  
Coverage Problems ◽  
Planning Problems ◽  
Coverage Planning

Motivated by the increasing appeal of robots in information-gathering missions, we study multi-agent path planning problems in which the agents must remain interconnected. We model an area by a topological graph specifying the movement and the connectivity constraints of the agents. We study the theoretical complexity of the reachability and the coverage problems of a fleet of connected agents on various classes of topological graphs. We establish the complexity of these problems on known classes, and introduce a new class called sight-moveable graphs which admit efficient algorithms.

Collaborative Scheduling of Algorithms for Path Planning of Unmanned Systems

2021 ◽  
Vol 01 ◽  
Author(s):  
Ying Li ◽  
Chubing Guo ◽  
Jianshe Wu ◽  
Xin Zhang ◽  
Jian Gao ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Reinforcement Learning ◽  
Path Planning ◽  
Unmanned Systems ◽  
Ant Colony Optimization Algorithm ◽  
A Algorithm ◽  
Collaborative Scheduling ◽  
Simulation Results ◽  
Planning Problems ◽  
Effective Path

Background: Unmanned systems have been widely used in multiple fields. Many algorithms have been proposed to solve path planning problems. Each algorithm has its advantages and defects and cannot adapt to all kinds of requirements. An appropriate path planning method is needed for various applications. Objective: To select an appropriate algorithm fastly in a given application. This could be helpful for improving the efficiency of path planning for Unmanned systems. Methods: This paper proposes to represent and quantify the features of algorithms based on the physical indicators of results. At the same time, an algorithmic collaborative scheme is developed to search the appropriate algorithm according to the requirement of the application. As an illustration of the scheme, four algorithms, including the A-star (A*) algorithm, reinforcement learning, genetic algorithm, and ant colony optimization algorithm, are implemented in the representation of their features. Results: In different simulations, the algorithmic collaborative scheme can select an appropriate algorithm in a given application based on the representation of algorithms. And the algorithm could plan a feasible and effective path. Conclusion: An algorithmic collaborative scheme is proposed, which is based on the representation of algorithms and requirement of the application. The simulation results prove the feasibility of the scheme and the representation of algorithms.

A survey on the application of path-planning algorithms for multi-rotor UAVs in precision agriculture

2022 ◽  
pp. 1-20
Author(s):  
Amin Basiri ◽  
Valerio Mariani ◽  
Giuseppe Silano ◽  
Muhammad Aatif ◽  
Luigi Iannelli ◽  
...  
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Flight Control ◽  
Precision Agriculture ◽  
Navigation Systems ◽  
Agricultural Crops ◽  
Cluttered Environments ◽  
Main Motivation ◽  
Autonomous Guidance ◽  
Planning Problems

Abstract Multi-rotor Unmanned Aerial Vehicles (UAVs), although originally designed and developed for defence and military purposes, in the last ten years have gained momentum, especially for civilian applications, such as search and rescue, surveying and mapping, and agricultural crops and monitoring. Thanks to their hovering and Vertical Take-Off and Landing (VTOL) capabilities and the capacity to carry out tasks with complete autonomy, they are now a standard platform for both research and industrial uses. However, while the flight control architecture is well established in the literature, there are still many challenges in designing autonomous guidance and navigation systems to make the UAV able to work in constrained and cluttered environments or also indoors. Therefore, the main motivation of this work is to provide a comprehensive and exhaustive literature review on the numerous methods and approaches to address path-planning problems for multi-rotor UAVs. In particular, the inclusion of a review of the related research in the context of Precision Agriculture (PA) provides a unified and accessible presentation for researchers who are initiating their endeavours in this subject.

Multi-Agent Form Closure Capture of a Generic 2D Polygonal Object Based on Projective Path Planning

2006 ◽  
Author(s):  
Pankaj Sharma ◽  
Anupam Saxena ◽  
Ashish Dutta
Keyword(s):  
Path Planning ◽  
Contact Point ◽  
Point Contact ◽  
Object Boundary ◽  
Actual Object ◽  
Contact Points ◽  
Correct Orientation ◽  
Novel Approach ◽  
Form Closure ◽  
Multi Agent

The study of multi-agent capture and manipulation of an object has been an area of active interest for many researchers. This paper presents a novel approach using Genetic Algorithm to determine the optimal contact points and the total number of agents (mobile robots) required to capture a stationary generic 2D polygonal object. After the goal points are determined the agents then reach their respective goals using a decentralized projective path planning algorithm. Form closure of the object is obtained using the concept of accessibility angle. The object boundary is first expanded and the robots reach the expanded object goal points and then converge on the actual object. This ensures that the agents reach the actual goal points at the same time and have the correct orientation. Frictionless point contact between the object and robots is assumed. The shape of the robot is considered a circle such that it can only apply force in outward radial direction from its center and along the normal to the object boundary at the contact point. Simulations results are presented that prove the effectiveness of the proposed method.

AGENT-BASED SYSTEM ARCHITECTURE FOR DYNAMIC AND OPEN ENVIRONMENTS

2003 ◽  
Vol 02 (01) ◽  
pp. 105-133 ◽  
Author(s):  
ELHADI SHAKSHUKI ◽  
HAMADA GHENNIWA ◽  
MAHAMED KAMEL
Keyword(s):  
System Architecture ◽  
Rapid Growth ◽  
Dynamic Environment ◽  
Information Gathering ◽  
Information Resources ◽  
Architecture Design ◽  
Agent Based ◽  
Interface Agents ◽  
Multi Agent ◽  
Computing Environments

The rapid growth of the network-centered (Internet and Intranet) computing environments requires new architectures for information gathering systems. Typically, in these environments, the information resources are dynamic, heterogeneous and distributed. In addition, these computing environments are open, where information resources may be connected or disconnected at any time. This paper presents an architecture for a multi-agent information gathering system. The architecture includes three types of agents: interface, broker and resource agents. The interface agents interact with the users to fulfill their interests and preferences. The resource agents access and capture the content of the information resources. The broker agents facilitate cooperation among the information and the resource agents to achieve their desired goals. This paper provides the agents' architecture, design and implementations that enable them to cooperate, coordinate and communicate with each other to gather information in an open and dynamic environment.

scholarly journals The Computational Complexity of Probabilistic Planning

1998 ◽  
Vol 9 ◽  
pp. 1-36 ◽  
Author(s):  
M. L. Littman ◽  
J. Goldsmith ◽  
M. Mundhenk
Keyword(s):  
Computational Complexity ◽  
Efficient Algorithms ◽  
Boolean Satisfiability ◽  
Complexity Classes ◽  
Probabilistic Planning ◽  
Plan Evaluation ◽  
Partially Ordered ◽  
Boolean Satisfiability Problem ◽  
Complete Problem ◽  
Planning Problems

We examine the computational complexity of testing and finding small plans in probabilistic planning domains with both flat and propositional representations. The complexity of plan evaluation and existence varies with the plan type sought; we examine totally ordered plans, acyclic plans, and looping plans, and partially ordered plans under three natural definitions of plan value. We show that problems of interest are complete for a variety of complexity classes: PL, P, NP, co-NP, PP, NP^PP, co-NP^PP, and PSPACE. In the process of proving that certain planning problems are complete for NP^PP, we introduce a new basic NP^PP-complete problem, E-MAJSAT, which generalizes the standard Boolean satisfiability problem to computations involving probabilistic quantities; our results suggest that the development of good heuristics for E-MAJSAT could be important for the creation of efficient algorithms for a wide variety of problems.

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