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Variable-Speed Dubins Orienteering Problem

Variable-Speed Dubins Orienteering Problem

引用

IEEE Latin American robotics Symposium, LARS

作者： L. C. Vinícius Faria C. G. Caio Ribeiro Douglas G. Macharet Department of Computer Science Computer Vision and Robotics Laboratory (VeRLab) Universidade Federal de Minas Gerais Belo Horizonte MG Brazil

ISBN: (数字)9798331508807

ISBN: (纸本)9798331508814

The class of vehicle routing problems plays an important role in optimizing logistics and transportation strategies across various sectors. In this context, the Orienteering Problem (OP) seeks to determine an optimized path through a set of locations with associated rewards, aiming to maximize the total collected reward while respecting constraints such as time or distance limits. Nonholonomic motion planning, particularly considering Dubins vehicles, is crucial in real-world applications due to its ability to accurately capture the constraints and dynamics of many physical vehicles. In this paper, we extend the Dubins Orienteering Problem (DOP), where unlike the classical Dubins model with constant speed, the vehicle can vary its speed during navigation, enabling the discovery of more effective paths. Experiments comparing both the DOP and our novel formulation show that the VS-DOP achieves higher total collected rewards within the same budget compared to the conventional DOP.

关键词： Navigation Vehicle routing Dynamics Transportation Planning Time factors Vehicle dynamics Robots Logistics

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Energy-Efficient Team Orienteering Problem in the Presence of Time-Varying Ocean Currents

Energy-Efficient Team Orienteering Problem in the Presence o...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Ariella Mansfield Douglas G. Macharet M. Ani Hsieh GRASP Laboratory University of Pennsylvania Philadelphia USA Department of Computer Science Computer Vision and Robotics Laboratory (VeRLab) Universidade Federal de Minas Gerais MG Brazil

Autonomous Marine Vehicles (AMVs) have gained interest for scientific and commercial applications, including pipeline and algae bloom monitoring, contaminant tracking, and ocean debris removal. The Team Orienteering Problem (TOP) is relevant in this context as Multi-Robot Systems (MRSs) allow for better coverage of the area of interest, simultaneous data collection at different locations, and an increase in the overall robustness and efficiency of the mission. However, route planning for AMVs in dynamic ocean environments is challenging due to the coupling of environmental and vehicle dynamics. We propose a multi-objective formulation that accounts for the trade-offs between visiting multiple task locations and energy consumption by the vehicles subject to a time budget. This work focuses on vehicles that can maintain a constant net speed but can be adapted to vehicles with constant thrust. Different from existing approaches, our method is able to leverage time-varying ocean currents to improve the energy efficiency of resulting routes. We validate our approach experimentally by superimposing ocean flow models with benchmark instances of the TOP.

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Social Space Segmentation for Approaching Tasks

Social Space Segmentation for Approaching Tasks

引用

IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Aline F. F. Silva Douglas G. Macharet Department of Computer Science Computer Vision and Robotics Laboratory (VeRLab) Universidade Federal de Minas Gerais Brazil Laboratório de Inteligência Computacional e Robótica (LICRo) Instituto Federal do Triângulo Mineiro (IFTM) Brazil

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

This paper introduces a novel methodology for the partitioning of the social space associated with arbitrary groups of individuals into approachable regions. The proposed method exploits boundary points within pre-identified social spaces and classifies them into three distinct levels based on the field of view between pairs of individuals within the group. The effectiveness of this approach was rigorously assessed across both static and dynamic scenarios, illustrating successful segmentation and classification of approachable regions. Furthermore, the methodology underwent comprehensive testing using publicly available datasets, yielding consistently satisfactory outcomes. This innovative approach represents a substantial contribution to the field of human-robot interaction, showcasing significant potential for future enhancements and advancements.

关键词： Human-robot interaction Robots Testing

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Efficiently Approaching Groups of People in a Socially Acceptable Manner in Environments with Obstacles

Efficiently Approaching Groups of People in a Socially Accep...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Aline F. F. Silva Luciano E. Almeida Douglas G. Macharet Department of Computer Science Computer Vision and Robotics Laboratory (VeRLab) Universidade Federal de Minas Gerais Brazil Laboratório de Inteligência Computacional e Robótica (LICRo) Instituto Federal do Triângulo Mineiro (IFTM) Brazil

Advancements in mobile robotics have allowed humans and robots to interact in different environments and ways. A problem of great interest in Human-Robot Interaction is how to approach individuals, e.g., to gather information, in a socially acceptable manner. We present a new method for planning sequential visits to various groups of people in cluttered environments. The problem is formulated as a Set Orienteering Problem, where each group denotes a cluster with a set of possible approaching points considering different F-formations. We use the concept of a social probabilistic roadmap to determine safe paths between groups. Simulations considering different cases show that methodology produces efficient tours that maximize the number of approached individuals while respecting social norms of distance and a limited budget.

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Adaptive Generalized Social Space Delimitation for Human-Robot Interaction Tasks

Adaptive Generalized Social Space Delimitation for Human-Rob...

引用

IEEE Latin American robotics Symposium, LARS

作者： Manuela M. F. Silva Aline F. F. Silva Douglas G. Macharet Department of Computer Science Computer Vision and Robotics Laboratory (VeRLab) Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Laboratório de Inteligência Computacional e Robótica (LICRo) Instituto Federal do Triângulo Mineiro (IFTM) Campus Patrocínio Brazil

ISBN: (数字)9798331508807

ISBN: (纸本)9798331508814

Human-Robot Interaction (HRI) research is of paramount importance as it addresses the rapidly evolving landscape where robots are increasingly integrated into everyday life. Social spaces refer to the invisible zones that individuals maintain around themselves, dictating appropriate distances for various types of interactions. This concept is pivotal in HRI, as it ensures that robots engage with humans in ways that are both comfortable and respectful of personal boundaries. In this paper, we propose a novel social space delimitation approach based on deformable elastic bands. Our method leverages the flexibility and adaptability of elastic band theory to dynamically define and adjust social spaces around individuals and groups. The results, based on both static and dynamic cases as well as a real-world dataset, show that our approach achieves a responsive and accurate representation of social spaces, that can accommodate varying group configurations and environmental conditions.

关键词： Accuracy Human-robot interaction Robots

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Energy-efficient Trajectory Planning with Media Transition for a Hybrid Unmanned Aerial-Underwater Vehicle

Energy-efficient Trajectory Planning with Media Transition f...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Pedro M. Pinheiro Armando Alves Neto Douglas G. Macharet Paulo L. J. Drews NAUTEC Center for Computational Science Universidade Federal do Rio Grande - FURG Rio Grande Brazil Dept. of Electronics Engineering Univ. Federal de Minas Gerais Belo Horizonte Brazil Dep. of Computer Science Computer Vision and Robotics Laboratory (VeRLab) Univ. Federal de Minas Gerais Belo Horizonte Brazil

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Vehicles capable of operating in more than one environment have been developed to solve real problems. Among them, the hybrid unmanned aerial-underwater vehicle (HUAUV) is receiving attention from the robotics community, mainly with a quadrotor-like configuration. However, this vehicle presents high energy consumption because of the larger mass required compared to the only aerial vehicle, limiting its autonomy. This work addresses the trajectory planning problem for a HUAUV. The method is based on Rapidly-exploring Random Trees (RRTs), a highly customizable planning technique. In addition, we propose two new heuristics to increase the energy efficiency of the hybrid vehicle. The first consists of biasing the tree expansion towards the environment with the lowest navigation cost, while the second one assigns estimated costs to nodes in the tree and chooses the least expensive trajectories. These techniques are evaluated in physically realistic simulation experiments performed in 135 scenarios. A comparative analysis of their performances is presented relative to the state of the art. We show that using efficient heuristics can significantly contribute to reducing energy consumption and even increase the average velocity in the missions performed by these vehicles.

关键词： Energy consumption Costs Limiting Trajectory planning Navigation Media Energy efficiency Trajectory Planning Intelligent robots

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A Routing-based Strategy to Socially Approach Multiple Individuals in Cluttered Environments

A Routing-based Strategy to Socially Approach Multiple Indiv...

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IEEE Latin American robotics Symposium, LARS

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

The use of autonomous mobile robots is expected to continue increasing in different parts of society in the next years. In this context, when not restricted to industrial environments only, it is essential to provide such devices with the ability to behave in a so-called socially acceptable manner. In the Human-Robot Interaction (HRI) field, a fundamental problem is to approach people, i.e., try to initiate and maintain an interaction. This task involves different challenges since some implicit nonverbal social rules must be respected, especially those concerning people's personal spaces (called proxemics). Considering the presence of multiple individuals to be approached, a combinatorial optimization aspect must also be tackled, where an optimal sequence of visits must be selected. In this paper, we formulate this problem as a Generalized Travelling Salesman Problem (GTSP) and combine it with a Probabilistic Roadmap (PRM) planner in order to account for obstacles in the environment. Numerical simulations show that the methodology produces length-optimized paths that are feasible, safe, and respect the social conventions.

关键词： Conferences Education Human-robot interaction Probabilistic logic Numerical simulation Space exploration Mobile robots

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Three-dimensional Terrain Aware Autonomous Exploration for Subterranean and Confined Spaces

Three-dimensional Terrain Aware Autonomous Exploration for S...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Héctor Azpúrna Mario F. M. Campos Douglas G. Macharet Computer Vision and Robotics Laboratory (VeRLab) Universidade Federal de Minas Gerais MG Brazil Instituto Tecnológico Vale (ITV) Ouro Preto Brazil

Despite the advances in autonomous navigation and motion planning, there are still several challenges to overcome, especially for confined or underground spaces. Confined scenarios present challenges such as lack of global or accurate external localization, uneven and slippery terrains, and multilevel stages. Exploring and mapping unknown unstructured environments is a fundamental step into the safe and efficient accomplishment of real-world tasks such as search and rescue missions or the autonomous inspection of dangerous areas. This paper proposes a novel three-dimensional autonomous exploration method for ground robots that considers the terrain traversability combined with the frontier expected information gain as a metric for the next best frontier selection in GPS-denied, confined spaces. Safe paths for navigation and frontier extraction are calculated iteratively from multiple 3D map representations such as octrees and meshes. Results in realistic simulated underground scenarios from the DARPA subterranean challenge demonstrate the technique's feasibility, achieving a more reliable and faster exploration rate over competing approaches.

关键词： Location awareness Three-dimensional displays Navigation Conferences Octrees Inspection Extraterrestrial measurements

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Anytime Fault-tolerant Adaptive Routing for Multi-Robot Teams

Anytime Fault-tolerant Adaptive Routing for Multi-Robot Team...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Ronaldo F. dos Santos Erickson R. Nascimento Douglas G. Macharet Computer Vision and Robotics Laboratory (VeRLab) Universidade Federal de Minas Gerais MG Brazil Tres Lagoas Campus Universidadeˆ Federal de Mato Grosso do Sul MS Brazil

The Correlated Team Orienteering Problem (CTOP) is a routing problem where the objective is to determine a set of routes that maximizes the summation of collected rewards in the environment while respecting the vehicles’ budget. However, solutions to this problem usually consider static instances and may produce poor results in dynamic real-world scenarios. In this paper, we propose an approach to deal with the execution of missions planned as a CTOP instance, especially when vehicles of the team are prone to failure and may not complete their routes. The main contribution of this paper is a novel anytime heuristic that iteratively adapts the initial set of routes, allowing to increase the overall robustness of the mission and still collect the most profitable rewards. The methodology was thoroughly evaluated considering different scenarios and in all the cases was able to achieve comparable or better results in terms of reward than planning a new set of routes, however, spending considerably less time.

关键词： Fault tolerance Automation Conferences Fault tolerant systems Routing Robustness Planning

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Adaptive Partitioning for Coordinated Multi-agent Perimeter Defense

Adaptive Partitioning for Coordinated Multi-agent Perimeter ...

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2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Douglas G. Macharet Austin K. Chen Daigo Shishika George J. Pappas Vijay Kumar GRASP Lab University of Pennsylvania Philadelphia USA Computer Vision and Robotics Laboratory (VeRLab) Universidade Federal de Minas Gerais Brazil

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

Multi-Robot Systems have been recently employed in different applications and have advantages over single-robot systems, such as increased robustness and task performance efficiency. We consider such assemblies specifically in the scenario of perimeter defense, where the task is to defend a circular perimeter by intercepting radially approaching targets. Possible intruders appear randomly at a fixed distance from the perimeter and with azimuthal location determined by some unknown probability density. Coordination among multiple defenders is a complex combinatorial optimization problem. In this work, we focus on the following two aspects: (i) estimating the probability density that describes the direction from which the next intruders are going to arrive, and (ii) partitioning of the space so that the defenders focus on capturing a disjoint subset of intruders. Results show that the proposed strategy increases the number of captures over a naive baseline strategy, especially in scenarios with non-uniform spatial distributions of intruder arrival. The proposed approach is also efficient and able to quickly adapt to time-varying intruder distributions.

关键词： Graphical models Robustness Multi-robot systems Task analysis Optimization Intelligent robots Distribution functions

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