GUARDIANS final report

Emergencies in industrial warehouses are a major concern for firefghters. The large dimensions together with the development of dense smoke that drastically reduces visibility, represent major challenges. The Guardians robot swarm is designed to assist fire fighters in searching a large warehouse. In this report we discuss the technology developed for a swarm of robots searching and assisting fire fighters. We explain the swarming algorithms which provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also one of the means to locate the robots and humans. Thus the robot swarm is able to locate itself and provide guidance information to the humans. Together with the re ghters we explored how the robot swarm should feed information back to the human fire fighter. We have designed and experimented with interfaces for presenting swarm based information to human beings

A robot swarm assisting a human fire-fighter

Emergencies in industrial warehouses are a major concern for fire-fighters. The large dimensions, together with the development of dense smoke that drastically reduces visibility, represent major challenges. The GUARDIANS robot swarm is designed to assist fire-fighters in searching a large warehouse. In this paper we discuss the technology developed for a swarm of robots assisting fire-fighters. We explain the swarming algorithms that provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also the means to locate the robots and humans. Thus, the robot swarm is able to provide guidance information to the humans. Together with the fire-fighters we explored how the robot swarm should feed information back to the human fire-fighter. We have designed and experimented with interfaces for presenting swarm-based information to human beings

Analysis on swarm robot coordination using fuzzy logic

In this paper, coordination among individual of swarm robot in communicating to maintain the safe distance between robots is analyzed. Each robot coordinates their movements to avoid obstacles and moving simultaneously. Evaluation of swarm robot performance is analyzed in this paper, namely: the coordination among robots to share information in safe distance determination. In controlling the coordination of motion, each robot has a sensor that provides several inputs about its surrounding environment. Fuzzy logic control in this paper allows uncertain input, and produces unlimited commands to control motion direction with speed settings according to environmental conditions. In this experiment, it is obtained that the size of the environment affects the coordination of robots

GUARDIANS final report part 1 (draft): a robot swarm assisting a human fire fighter

Emergencies in industrial warehouses are a major concern for fire fighters. The large dimensions together with the development of dense smoke that drastically reduces visibility, represent major challenges. The Guardians robot swarm is designed to assist re ghters in searching a large warehouse. In this paper we discuss the technology developed for a swarm of robots assisting re ghters. We explain the swarming algorithms which provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also the means to locate the robots and humans. Thus the robot swarm is able to provide guidance information to the humans. Together with the fire fighters we explored how the robot swarm should feed information back to the human fire fighter. We have designed and experimented with interfaces for presenting swarm based information to human beings

Analysis on swarm robot coordination using fuzzy logic

In this paper, coordination among individual of swarm robot in communicating to maintain the safe distance between robots is analyzed. Each robot coordinates their movements to avoid obstacles and moving simultaneously. Evaluation of swarm robot performance is analyzed in this paper, namely: the coordination among robots to share information in safe distance determination. In controlling the coordination of motion, each robot has a sensor that provides several inputs about its surrounding environment. Fuzzy logic control in this paper allows uncertain input, and produces unlimited commands to control motion direction with speed settings according to environmental conditions. In this experiment, it is obtained that the size of the environment affects the coordination of robots

An Integrated Testbed for Cooperative Perception with Heterogeneous Mobile and Static Sensors

Cooperation among devices with different sensing, computing and communication capabilities provides interesting possibilities in a growing number of problems and applications including domotics (domestic robotics), environmental monitoring or intelligent cities, among others. Despite the increasing interest in academic and industrial communities, experimental tools for evaluation and comparison of cooperative algorithms for such heterogeneous technologies are still very scarce. This paper presents a remote testbed with mobile robots and Wireless Sensor Networks (WSN) equipped with a set of low-cost off-the-shelf sensors, commonly used in cooperative perception research and applications, that present high degree of heterogeneity in their technology, sensed magnitudes, features, output bandwidth, interfaces and power consumption, among others. Its open and modular architecture allows tight integration and interoperability between mobile robots and WSN through a bidirectional protocol that enables full interaction. Moreover, the integration of standard tools and interfaces increases usability, allowing an easy extension to new hardware and software components and the reuse of code. Different levels of decentralization are considered, supporting from totally distributed to centralized approaches. Developed for the EU-funded Cooperating Objects Network of Excellence (CONET) and currently available at the School of Engineering of Seville (Spain), the testbed provides full remote control through the Internet. Numerous experiments have been performed, some of which are described in the paper

Collaborative Multi-Robot Search and Rescue: Planning, Coordination, Perception, and Active Vision

Search and rescue (SAR) operations can take significant advantage from supporting autonomous or teleoperated robots and multi-robot systems. These can aid in mapping and situational assessment, monitoring and surveillance, establishing communication networks, or searching for victims. This paper provides a review of multi-robot systems supporting SAR operations, with system-level considerations and focusing on the algorithmic perspectives for multi-robot coordination and perception. This is, to the best of our knowledge, the first survey paper to cover (i) heterogeneous SAR robots in different environments, (ii) active perception in multi-robot systems, while (iii) giving two complementary points of view from the multi-agent perception and control perspectives. We also discuss the most significant open research questions: shared autonomy, sim-to-real transferability of existing methods, awareness of victims' conditions, coordination and interoperability in heterogeneous multi-robot systems, and active perception. The different topics in the survey are put in the context of the different challenges and constraints that various types of robots (ground, aerial, surface, or underwater) encounter in different SAR environments (maritime, urban, wilderness, or other post-disaster scenarios). The objective of this survey is to serve as an entry point to the various aspects of multi-robot SAR systems to researchers in both the machine learning and control fields by giving a global overview of the main approaches being taken in the SAR robotics area

Neuro-Dominating Set Scheme for a Fast and Efficient Robot Deployment in Internet of Robotic Things

International audienceInternet of Robotic Things (IoRT) is a new concept introduced for the first time by ABI Research. Unlike the Internet of Things (IoT), IoRT provides an active sensorization and is considered as the new evolution of IoT. In this context, we propose a Neuro-Dominating Set algorithm (NDS) to efficiently deploy a team of mobile wireless robots in an IoRT scenario, in order to reach a desired inter-robot distance, while maintaining global connectivity in the whole network. We use the term Neuro-Dominating Set to describe our approach, since it is inspired by both neural network and dominating set principles. With NDS algorithm, a robot adopts different behaviors according whether it is a dominating or a dominated robot. Our main goal is to show and demonstrate the beneficial effect of using different behaviors in the IoRT concept. The obtained results show that the proposed method outperforms an existing related technique (i.e., the Virtual Angular Force approach) and the neural network based approach presented in our previous work. As an objective, we aim to decrease the overall traveled distance and keep a low energy consumption level, while maintaining network connectivity and an acceptable convergence time

Marsupial 로봇 팀의 효율적인 배치 및 회수를 위한 경로 계획에 관한 연구

학위논문 (박사)-- 서울대학교 대학원 공과대학 전기·컴퓨터공학부, 2017. 8. 이범희.This dissertation presents time-efficient approaches to path planning for initial deployment and collection of a heterogeneous marsupial robot team consists of a large-scale carrier robot and multiple mobile robots. Although much research has been conducted about task allocation and path planning of multi-robot systems, the path planning problems for deployment and collection of a marsupial robot team have not been fully addressed. The objectives of the problems are to minimize the duration that mobile robots require to reach their assigned task locations and return from those locations. Taking the small mobile robot's energy constraint into account, a large-scale carrier robot, which is faster than a mobile robot, is considered for efficient deployment and collection. The carrier robot oversees transporting, deploying, and retrieving of mobile robots, whereas the mobile robots are responsible for carrying out given tasks such as reconnaissance and search and rescue. The path planning methods are introduced in both an open space without obstacles and a roadmap graph which avoids obstacles. For the both cases, determining optimal path requires enormous search space whose computational complexity is equivalent to solving a combinatorial optimization problem. To reduce the amount of computation, both task locations and mobile robots to be collected are divided into a number of clusters according to their geographical adjacency and their energies. Next, the cluster are sorted based on the location of the carrier robot. Then, an efficient path for the carrier robot can be generated by traveling to each deploying and loading location relevant to each cluster. The feasibility of the proposed algorithms is demonstrated through several simulations in various environments including three-dimensional space and dynamic task environment. Finally, the performance of the proposed algorithms is also demonstrated by comparing with other simple methods.Chapter 1 Introduction 1 1.1 Background and motivation 1 1.1.1 Multi-robot system 1 1.1.2 Marsupial robot team 3 1.2 Contributions of the thesis 9 Chapter 2 Related Work 13 2.1 Multi-robot path planning 14 2.2 Multi-robot exploration 14 2.3 Multi-robot task allocation 15 2.4 Simultaneous localization and mapping 15 2.5 Motion planning of collective swarm 16 2.6 Marsupial robot team 18 2.6.1 Multi-robot deployment 18 2.6.2 Marsupial robot 19 2.7 Robot collection 23 2.8 Roadmap generation 24 2.8.1 Geometric algorithms 24 2.8.2 Sampling-based algorithms 25 2.9 Novelty of the thesis 26 Chapter 3 Preliminaries 27 3.1 Notation 27 3.2 Assumptions 29 3.3 Clustering algorithm 30 3.4 Minimum bounded circle and sphere of a cluster 32 Chapter 4 Deployment of a Marsupial Robot Team 35 4.1 Problem definition 35 4.2 Complexity analysis 37 4.3 Optimal deployment path planning for two tasks 38 4.3.1 Deployment for two tasks in 2D space 39 4.3.2 Deployment for two tasks in 3D space 41 4.4 Path planning algorithm of a marsupial robot team for deployment 42 4.5 Simulation result 49 4.5.1 Simulation setup 49 4.5.2 Deployment scenarios in 2D space 50 4.5.3 Deployment scenarios in 3D space 57 4.5.4 Deployment in a dynamic environment 60 4.6 Performance evaluation 62 4.6.1 Computation time 62 4.6.2 Efficiency of the path 64 Chapter 5 Collection of a Marsupial Robot Team 67 5.1 Problem definition 68 5.2 Complexity analysis 70 5.3 Optimal collection path planning for two rovers 71 5.3.1 Collection for two rovers in 2D space 71 5.3.2 Collection for two rovers in 3D space 75 5.4 Path planning algorithm of a marsupial robot team for collection 76 5.5 Simulation result 83 5.5.1 Collection scenarios in 2D space 83 5.5.2 Collection scenarios in 3D space 88 5.5.3 Collection in a dynamic environment 91 5.6 Performance evaluation 93 5.6.1 Computation time 93 5.6.2 Efficiency of the path 95 Chapter 6 Deployment of a Marsupial Robot Team using a Graph 99 6.1 Problem definition 99 6.2 Framework 101 6.3 Probabilistic roadmap generation 102 6.3.1 Global PRM 103 6.3.2 Local PRM 105 6.4 Path planning strategy 105 6.4.1 Clustering scheme 106 6.4.2 Determining deployment locations 109 6.4.3 Path smoothing 113 6.4.4 Path planning algorithm for a marsupial robot team 115 6.5 Simulation result 116 6.5.1 Outdoor space without obstacle 116 6.5.2 Outdoor space with obstacles 118 6.5.3 Office area 119 6.5.4 University research building 122 Chapter 7 Conclusion 125 Bibliography 129 초록 151Docto