TRIFFID: Autonomous Robotic Aid For Increasing First Responders Efficiency
- URL: http://arxiv.org/abs/2502.09379v1
- Date: Thu, 13 Feb 2025 14:46:40 GMT
- Title: TRIFFID: Autonomous Robotic Aid For Increasing First Responders Efficiency
- Authors: Jorgen Cani, Panagiotis Koletsis, Konstantinos Foteinos, Ioannis Kefaloukos, Lampros Argyriou, Manolis Falelakis, Iván Del Pino, Angel Santamaria-Navarro, Martin Čech, Ondřej Severa, Alessandro Umbrico, Francesca Fracasso, AndreA Orlandini, Dimitrios Drakoulis, Evangelos Markakis, Georgios Th. Papadopoulos,
- Abstract summary: This paper introduces the TRIFFID system, which integrates unmanned ground and aerial vehicles with advanced artificial intelligence functionalities.
The proposed system enhances emergency response teams by providing advanced mission planning, safety monitoring, and adaptive task execution capabilities.
- Score: 33.20746728498466
- License:
- Abstract: The increasing complexity of natural disaster incidents demands innovative technological solutions to support first responders in their efforts. This paper introduces the TRIFFID system, a comprehensive technical framework that integrates unmanned ground and aerial vehicles with advanced artificial intelligence functionalities to enhance disaster response capabilities across wildfires, urban floods, and post-earthquake search and rescue missions. By leveraging state-of-the-art autonomous navigation, semantic perception, and human-robot interaction technologies, TRIFFID provides a sophisticated system com- posed of the following key components: hybrid robotic platform, centralized ground station, custom communication infrastructure, and smartphone application. The defined research and development activities demonstrate how deep neural networks, knowledge graphs, and multimodal information fusion can enable robots to autonomously navigate and analyze disaster environ- ments, reducing personnel risks and accelerating response times. The proposed system enhances emergency response teams by providing advanced mission planning, safety monitoring, and adaptive task execution capabilities. Moreover, it ensures real- time situational awareness and operational support in complex and risky situations, facilitating rapid and precise information collection and coordinated actions.
Related papers
- Soft Robotics for Search and Rescue: Advancements, Challenges, and Future Directions [0.0]
This paper critically examines advancements in soft robotic technologies tailored for Search and Rescue (SAR) applications.
By leveraging bio-inspired designs, flexible materials, and advanced locomotion mechanisms, soft robots demonstrate exceptional potential in disaster scenarios.
arXiv Detail & Related papers (2025-02-17T23:24:18Z) - An Integrated Artificial Intelligence Operating System for Advanced Low-Altitude Aviation Applications [4.62967829580797]
This paper introduces a high-performance artificial intelligence operating system tailored for low-altitude aviation.
It addresses key challenges such as real-time task execution, computational efficiency, and seamless modular collaboration.
arXiv Detail & Related papers (2024-11-28T01:24:16Z) - Evacuation Management Framework towards Smart City-wide Intelligent
Emergency Interactive Response System [6.318200538258479]
We propose a set of coordinated technological solutions to transform an existing emergency response system into an intelligent interactive system.
This smart interactive response system will benefit from advanced sensor fusion and AI by formulating a real time dynamic model.
arXiv Detail & Related papers (2024-03-07T12:10:19Z) - Rapid post-disaster infrastructure damage characterisation enabled by remote sensing and deep learning technologies -- a tiered approach [0.4837072536850576]
Transport networks and bridges are systematically targeted during wars and suffer damage during natural disasters.
No methods exist for automated characterisation of damage at multiple scales.
We propose an integrated, multi-scale tiered approach to fill this capability gap.
arXiv Detail & Related papers (2024-01-31T11:36:12Z) - Camera-Radar Perception for Autonomous Vehicles and ADAS: Concepts,
Datasets and Metrics [77.34726150561087]
This work aims to carry out a study on the current scenario of camera and radar-based perception for ADAS and autonomous vehicles.
Concepts and characteristics related to both sensors, as well as to their fusion, are presented.
We give an overview of the Deep Learning-based detection and segmentation tasks, and the main datasets, metrics, challenges, and open questions in vehicle perception.
arXiv Detail & Related papers (2023-03-08T00:48:32Z) - ADAPT: An Open-Source sUAS Payload for Real-Time Disaster Prediction and
Response with AI [55.41644538483948]
Small unmanned aircraft systems (sUAS) are becoming prominent components of many humanitarian assistance and disaster response operations.
We have developed the free and open-source ADAPT multi-mission payload for deploying real-time AI and computer vision onboard a sUAS.
We demonstrate the example mission of real-time, in-flight ice segmentation to monitor river ice state and provide timely predictions of catastrophic flooding events.
arXiv Detail & Related papers (2022-01-25T14:51:19Z) - Autonomous Aerial Robot for High-Speed Search and Intercept Applications [86.72321289033562]
A fully-autonomous aerial robot for high-speed object grasping has been proposed.
As an additional sub-task, our system is able to autonomously pierce balloons located in poles close to the surface.
Our approach has been validated in a challenging international competition and has shown outstanding results.
arXiv Detail & Related papers (2021-12-10T11:49:51Z) - AI Agents in Emergency Response Applications [0.0]
Emergency personnel respond to various situations ranging from fire, medical, hazardous materials, industrial accidents, to natural disasters.
Mission-critical "edge AI" situations require low-latency, reliable analytics.
We propose an agent-based architecture for deployment of AI agents via 5G service-based architecture.
arXiv Detail & Related papers (2021-09-10T03:24:50Z) - AI in Smart Cities: Challenges and approaches to enable road vehicle
automation and smart traffic control [56.73750387509709]
SCC ideates on a data-centered society aiming at improving efficiency by automating and optimizing activities and utilities.
This paper describes AI perspectives in SCC and gives an overview of AI-based technologies used in traffic to enable road vehicle automation and smart traffic control.
arXiv Detail & Related papers (2021-04-07T14:31:08Z) - Simultaneous Navigation and Construction Benchmarking Environments [73.0706832393065]
We need intelligent robots for mobile construction, the process of navigating in an environment and modifying its structure according to a geometric design.
In this task, a major robot vision and learning challenge is how to exactly achieve the design without GPS.
We benchmark the performance of a handcrafted policy with basic localization and planning, and state-of-the-art deep reinforcement learning methods.
arXiv Detail & Related papers (2021-03-31T00:05:54Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.