Multi-Robot Collaborative Reasoning for Unique Person Recognition in Complex Environments

2020 ◽  
Author(s):  
Chule Yang ◽  
Yufeng Yue ◽  
Mingxing Wen ◽  
Yuanzhe Wang ◽  
Baosong Deng
Keyword(s):  
Complex Environments ◽  
Collaborative Reasoning ◽  
Person Recognition ◽  
Multi Robot

scholarly journals CHORD: Distributed Data-sharing via Hybrid ROS 1 and 2 for Multi-robot Exploration of Large-scale Complex Environments

2021 ◽  
pp. 1-1
Author(s):  
Muhammad Fadhil Ginting ◽  
Kyohei Otsu ◽  
Jeffrey Edlund ◽  
Jay Gao ◽  
Ali-akbar Agha-mohammadi
Keyword(s):  
Data Sharing ◽  
Large Scale ◽  
Distributed Data ◽  
Complex Environments ◽  
Multi Robot

scholarly journals Applications of DEC-MDPs in Multi-Robot Systems

Robotics ◽  
2013 ◽  
pp. 143-165
Author(s):  
Aurélie Beynier ◽  
Abdel-Illah Mouaddib
Keyword(s):  
Decentralized Control ◽  
Decision Processes ◽  
Decision Problems ◽  
Large Set ◽  
Complex Environments ◽  
Uncertain Environments ◽  
Robot Systems ◽  
Markov Decision ◽  
Partially Observable ◽  
Multi Robot

Optimizing the operation of cooperative multi-robot systems that can cooperatively act in large and complex environments has become an important focal area of research. This issue is motivated by many applications involving a set of cooperative robots that have to decide in a decentralized way how to execute a large set of tasks in partially observable and uncertain environments. Such decision problems are encountered while developing exploration rovers, teams of patrolling robots, rescue-robot colonies, mine-clearance robots, et cetera. In this chapter, we introduce problematics related to the decentralized control of multi-robot systems. We first describe some applicative domains and review the main characteristics of the decision problems the robots must deal with. Then, we review some existing approaches to solve problems of multiagent decentralized control in stochastic environments. We present the Decentralized Markov Decision Processes and discuss their applicability to real-world multi-robot applications. Then, we introduce OC-DEC-MDPs and 2V-DEC-MDPs which have been developed to increase the applicability of DEC-MDPs.

A Framework for Prototyping of Autonomous Multi-Robot Systems for Search, Rescue, and Reconnaissance

2012 ◽  
pp. 407-437
Author(s):  
Sedat Dogru ◽  
Sebahattin Topal ◽  
Aydan M. Erkmen ◽  
Ismet Erkmen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Search And Rescue ◽  
Wireless Sensor ◽  
Complex Environments ◽  
Robot Systems ◽  
Design Characteristics ◽  
Hardware Platforms ◽  
Connectivity Maintenance ◽  
Multi Robot

Robots consistently help humans in dangerous and complex tasks by providing information about, and executing tasks in disaster areas that are highly unstructured, uncertain, possibly hostile, and sometimes not reachable to humans directly. Prototyping autonomous multi-robot systems in disaster scenarios both as hardware platforms and software can provide foundational infrastructure in comparing performance of different methodologies developed for search, rescue, monitoring and reconnaissance. In this chapter, the authors discuss prototyping modules of heterogeneous multi-robot networks and their design characteristics for two different scenarios, namely Search and Rescue in unstructured complex environments, and connectivity maintenance in Sycophant Wireless Sensor Networks which are static ecto-parasitic clandestine sensor networks mounted incognito on mobile agents using only the agent’s mobility without intervention, and are cooperating with sparse mobile robot sensor networks.

scholarly journals Multi-Robot Motion Planning with Dynamics Guided by Multi-Agent Search

2018 ◽  
Author(s):  
Duong Le ◽  
Erion Plaku
Keyword(s):  
Nonlinear Dynamics ◽  
Physical World ◽  
The Other ◽  
Robot Motion ◽  
Robot Motion Planning ◽  
Complex Environments ◽  
Continuous State Space ◽  
Continuous State ◽  
Multi Agent ◽  
Multi Robot

This paper presents an effective multi-robot motion planner that enables each robot to reach its desired location while avoiding collisions with the other robots and the obstacles. The approach takes into account the differential constraints imposed by the underlying dynamics of each robot and generates dynamically-feasible motions that can be executed in the physical world. The crux of the approach is the sampling-based expansion of a motion tree in the continuous state space of all the robots guided by multi-agent search over a discrete abstraction. Experiments using vehicle models with nonlinear dynamics operating in complex environments show significant speedups over related work.

scholarly journals Extended rapidly exploring random tree–based dynamic path planning and replanning for mobile robots

2018 ◽  
Vol 15 (3) ◽  
pp. 172988141877387 ◽  
Author(s):  
Devin Connell ◽  
Hung Manh La
Keyword(s):  
Path Planning ◽  
Search Tree ◽  
Random Tree ◽  
Complex Environments ◽  
Operational Environment ◽  
Moving Obstacles ◽  
Dynamic Path Planning ◽  
Current Location ◽  
Current Plan ◽  
Multi Robot

It is necessary for a mobile robot or even a multi-robot team to be able to efficiently plan a path from its starting or current location to a desired goal location. This is a trivial task when the environment is static. However, the operational environment of the robot is rarely static, and it often has many moving obstacles. The robot may encounter one, or many, of these unknown and unpredictable moving obstacles. The robot will need to decide how to proceed when one of these obstacles is obstructing its path. In this article, a new method of dynamic replanning is proposed to allow the robot to efficiently plan a path in such complex environments. Our proposed replanning method is based on an extended rapidly exploring random tree. The robot will modify its current plan when unknown random moving obstacles obstruct the path. We extend the proposed replanning method to multi-robot scenarios in which the ability to share path planning and search tree information is valuable. An efficient method of node sharing is proposed to allow the multi-robot team to quickly develop path plans. Various experimental results in both single and multi-robot scenarios show the effectiveness of the proposed methods.

scholarly journals Hybrid Insect-Inspired Multi-Robot Coverage in Complex Environments

2015 ◽  
pp. 56-68 ◽  
Author(s):  
Bastian Broecker ◽  
Ipek Caliskanelli ◽  
Karl Tuyls ◽  
Elizabeth I. Sklar ◽  
Daniel Hennes
Keyword(s):  
Complex Environments ◽  
Multi Robot

scholarly journals A Framework for Prototyping of Autonomous Multi-Robot Systems for Search, Rescue, and Reconnaissance

Robotics ◽  
2013 ◽  
pp. 112-142
Author(s):  
Sedat Dogru ◽  
Sebahattin Topal ◽  
Aydan M. Erkmen ◽  
Ismet Erkmen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Search And Rescue ◽  
Wireless Sensor ◽  
Complex Environments ◽  
Robot Systems ◽  
Design Characteristics ◽  
Hardware Platforms ◽  
Connectivity Maintenance ◽  
Multi Robot

Robots consistently help humans in dangerous and complex tasks by providing information about, and executing tasks in disaster areas that are highly unstructured, uncertain, possibly hostile, and sometimes not reachable to humans directly. Prototyping autonomous multi-robot systems in disaster scenarios both as hardware platforms and software can provide foundational infrastructure in comparing performance of different methodologies developed for search, rescue, monitoring and reconnaissance. In this chapter, the authors discuss prototyping modules of heterogeneous multi-robot networks and their design characteristics for two different scenarios, namely Search and Rescue in unstructured complex environments, and connectivity maintenance in Sycophant Wireless Sensor Networks which are static ecto-parasitic clandestine sensor networks mounted incognito on mobile agents using only the agent’s mobility without intervention, and are cooperating with sparse mobile robot sensor networks.

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