Search Results (11)

This study presents an integrated design methodology for earthquake demolition rescue robots by combining UXMs, Kano, and QFD to improve design rationality and performance in extreme rescue scenarios. It addresses key gaps in existing approaches, particularly the lack of systematic experiential data acquisition, quantitative requirement analysis, and effective design translation. UXMs are applied to reconstruct critical task scenarios and identify high-load nodes and user experience variations. The Kano model is used to prioritise and classify user requirements, which are then translated into engineering characteristics through QFD. Based on this framework, a conceptual robot design is developed using the FBS model and evaluated through process-level simulation and usability assessment. The results demonstrate that the proposed method enables structured requirement transformation and supports traceable design decisions. Simulation indicates the consistency of task workflows and coordination among functional modules at the process level. A System Usability Scale score of 80.22 indicates a relatively high level of perceived usability at the conceptual evaluation stage. The proposed methodology provides a structured and traceable conceptual design framework for earthquake rescue robots. While the current validation is based on conceptual-level evaluation, the methodology offers a traceable design pathway that may be extended to other high-risk emergency equipment with further empirical testing. Full article

The reliable and efficient navigation for mobile robots across challenging outdoor terrains is critical for autonomous robotics. Traditional methods for planning the path of such robots often emphasize minimizing the travel distance but do not accommodate terrain stability, variability, or energy efficiency. The study proposes an integrated approach between satellite-driven geolocation data and terrain-specific features that enhance the path planning strategies in complex outdoor environments. Our method proposes a controller that uses search-based algorithms to generate energy-efficient and dynamically stable trajectories incorporating surface characteristics and environmental data from satellite imagery. By integrating our method, the proposed framework identifies safer and more reliable routes, achieving a significant 32% improvement in traction characteristics compared to the conventional models of path-finding approaches. Our method’s benefits over traditional approaches include improved safety, extended operational efficiency, and the ability to navigate unpredictable and dynamic environments. This makes it ideal for planetary exploration, disaster response in landslide-prone areas, agricultural automation for precision farming in rough terrains, search and rescue operations in earthquake-affected areas, and autonomous delivery systems navigation into rural and unstructured landscapes. It redefines autonomous navigation through terrain-aware planning and delivers a robust performance approach in unpredictable and dynamic environments. Full article

To effectively enhance the adaptability of earthquake rescue robots in dynamic environments and complex tasks, there is an urgent need for a comprehensive evaluation method that encompasses establishing an evaluation index system, testing performance indexes, and conducting performance evaluation. Firstly, four main criterion and twenty-three sub-criterion indexes are established by conducting a comprehensive review of existing assessment measures for rescue robots across diverse domains. These indexes are validated through test modules developed by the National Earthquake Response Support Service to obtain corresponding values for each criterion. Moreover, a method for establishing the index system is proposed based on the fuzzy clustering analysis and grey correlation analysis methods. This method effectively addresses issues related to excessive subjectivity, redundancy, and ambiguous stratification of indexes. Subsequently, the DEMATEL is employed to scrutinize the interrelationships and causal connections among each index within the established index system, leading to the identification of input and output indexes based on the analysis outcomes. Finally, as an empirical example, three earthquake rescue robots are comprehensively evaluated and ranked using the super efficiency DEA model. Alongside analyzing results regarding input redundancy and output deficiency, targeted improvement suggestions are provided for each earthquake rescue robot. Additionally, comparison analysis with the entropy weight method and VIKOR method verifies the effectiveness of our proposed method. Full article

To effectively enhance the adaptability of earthquake rescue robots in dynamic environments and complex tasks, there is an urgent need for an evaluation method that quantifies their performance and facilitates the selection of rescue robots with optimal overall capabilities. In this paper, twenty-two evaluation criteria are proposed based on a comprehensive review of existing evaluation criteria for rescue robots across various domains. The evaluation criteria are tested using the test modules developed by the National Earthquake Response support service, obtaining the corresponding values for each criterion. Then, the weights of the criterion layer and comprehensive evaluation index are determined based on the analytical hierarch process and trapezoidal fuzzy number complementary judgment matrix, and a new consistency test method is proposed. The qualitative evaluation and quantitative analysis are effectively combined to overcome the subjective influence of expert decision-making. Additionally, the performance of three earthquake search and rescue robots is comprehensively evaluated and ranked using the improved radar chart method as an empirical example. Finally, the robustness of the ranking results is examined using a weight sensitivity analysis. The results of the sensitivity analysis demonstrate the effectiveness and feasibility of the proposed method, thereby providing valuable insights for developing multi-objective optimization control strategies and structural designs for earthquake search and rescue robots. Full article

Natural disasters such as earthquakes, floods, and forest fires involve critical situations in which human lives and infrastructures are in jeopardy. People are often injured and/or trapped without being able to be assisted by first responders on time. Moreover, in most cases, the harsh environment jeopardizes first responders by significantly increasing the difficulty of their mission. In such scenarios, time is crucial and often of vital importance. First responders must have a clear and complete view of the current situation every few seconds/minutes to efficiently and timely tackle emerging challenges, ensuring the safety of both victims and personnel. Advances in related technology including robots, drones, and Internet of Things (IoT)-enabled equipment have increased their usability and importance in life- and time-critical decision support systems such as the ones designed and developed for Search and Rescue (SAR) missions. Such systems depend on efficiency in their ability to integrate large volumes of heterogeneous and streaming data and reason with this data in (near) real time. In addition, real-time critical data integration and reasoning need to be performed on edge devices that reside near the missions, instead of using cloud infrastructure. The aim of this paper is twofold: (a) to review technologies and approaches related to real-time semantic data integration and reasoning on IoT-enabled collaborative entities and edge devices in life- and time-critical decision support systems, with a focus on systems designed for SAR missions and (b) to identify open issues and challenges focusing on the specific topic. In addition, this paper proposes a novel approach that will go beyond the state-of-the-art in efficiently recognizing time-critical high-level events, supporting commanders and first responders with meaningful and life-critical insights about the current and predicted state of the environment in which they operate. Full article

Natural disasters, including earthquakes, floods, landslides, tsunamis, wildfires, and hurricanes, have become more common in recent years due to rapid climate change. For Post-Disaster Management (PDM), authorities deploy various types of user equipment (UE) for the search and rescue operation, for example, search and rescue robots, drones, medical robots, smartphones, etc., via the Internet of Robotic Things (IoRT) supported by cellular 4G/LTE/5G and beyond or other wireless technologies. For uninterrupted communication services, movable and deployable resource units (MDRUs) have been utilized where the base stations are damaged due to the disaster. In addition, power optimization of the networks by satisfying the quality of service (QoS) of each UE is a crucial challenge because of the electricity crisis after the disaster. In order to optimize the energy efficiency, UE throughput, and serving cell (SC) throughput by considering the stationary as well as movable UE without knowing the environmental priori knowledge in MDRUs aided two-tier heterogeneous networks (HetsNets) of IoRT, the optimization problem has been formulated based on emitting power allocation and user association combinedly in this article. This optimization problem is nonconvex and NP-hard where parameterized (discrete: user association and continuous: power allocation) action space is deployed. The new model-free hybrid action space-based algorithm called multi-pass deep Q network (MP-DQN) is developed to optimize this complex problem. Simulations results demonstrate that the proposed MP-DQN outperforms the parameterized deep Q network (P-DQN) approach, which is well known for solving parameterized action space, DQN, as well as traditional algorithms in terms of reward, average energy efficiency, UE throughput, and SC throughput for motionless as well as moveable UE. Full article

Every year, especially in urban areas, the population density rises quickly. The effects of catastrophes (i.e., war, earthquake, fire, tsunami) on people are therefore significant and grave. Assisting the impacted people will soon involve human-robot Search and Rescue (SAR) operations. Therefore, it is crucial to connect contemporary technology (i.e., robots and cognitive approaches) to SAR to save human lives. However, these operations also call for careful consideration of several factors, including safety, severity, and resources. Hence, ethical issues with technologies in SAR must be taken into consideration at the development stage. In this study, the most relevant ethical and design issues that arise when using robotic and cognitive technology in SAR are discussed with a focus on the response phase. Among the vast variety of SAR robots that are available nowadays, snake robots have shown huge potential; as they could be fitted with sensors and used for transporting tools to hazardous or confined areas that other robots and humans are unable to access. With this perspective, particular emphasis has been put on snake robotics in this study by considering ethical and design issues. This endeavour will contribute to providing a broader knowledge of ethical and technological factors that must be taken into account throughout the design and development of snake robots. Full article

This paper considers the issue of the search and rescue operation of humans after natural or man-made disasters. This problem arises after several calamities, such as earthquakes, hurricanes, and explosions. It usually takes hours to locate the survivors in the debris. In most cases, it is dangerous for the rescue workers to visit and explore the whole area by themselves. Hence, there is a need for speeding up the whole process of locating survivors accurately and with less damage to human life. To tackle this challenge, we present a scalable solution. We plan to introduce the usage of robots for the initial exploration of the calamity site. The robots will explore the site and identify the location of human survivors by examining the video feed (with audio) captured by them. They will then stream the detected location of the survivor to a centralized cloud server. It will also monitor the associated air quality of the selected area to determine whether it is safe for rescue workers to enter the region or not. The human detection model for images that we have used has a mAP (mean average precision) of 70.2%. The proposed approach uses a speech detection technique which has an F1 score of 0.9186 and the overall accuracy of the architecture is 95.83%. To improve the detection accuracy, we have combined audio detection and image detection techniques. Full article

Occasionally, professional rescue teams encounter issues while rescuing people during earthquake collapses. One such issue is the localization of wounded people from the earthquake. Machines used by rescue teams may cause crucial issues due to misleading localization. Usually, robot technology is utilized to address this problem. Many research papers addressing rescue operations have been published in the last two decades. In the literature, there are few studies on multi-robot coordination. The systems designed with a single robot should also overcome time constraints. A sophisticated algorithm should be developed for multi-robot coordination to solve that problem. Then, a fast rescuing operation could be performed. The distinctive property of this study is that it proposes a multi-robot system using a novel heuristic bat-inspired algorithm for use in search and rescue operations. Bat-inspired techniques gained importance in soft-computing experiments. However, there are only single-robot systems for robot navigation. Another original aspect of this paper is that this heuristic algorithm is employed to coordinate the robots. The study is devised to encourage extended work related to earthquake collapse rescue operations. Full article

Conventional motors with complicated electromagnetic structures are difficult to miniaturise for millimetre- and centimetre-sized robots. Instead, small-scale robots are actuated using a variety of functional materials. We proposed a novel robot propelled by a piezoelectric ceramic in this work. The robot advances due to the asymmetric friction created by the spikes on the surface. The structural modelling was completed, static and dynamic models were established to predict the moving characteristics, the prototype was built using three dimensional (3D) printing technology, and the models were evaluated via experiments. Compared with conventional inchworm-type robots, the proposed robot is superior in simple structure because the clamping components are replaced by spikes with asymmetric friction. Compared with SMA (shape memory alloy) actuating inchworm-type robots, it has a faster velocity with higher resolution. Meanwhile, the components are printed through an additive manufacturing process that is convenient and avoids assembly errors. This design could make contributions to many areas, such as pipe inspection, earthquake rescue, and medicine delivery. Full article

In some hazardous or inaccessible applications, such as earthquake rescue, as a substitute for mankind, robots are expected to perform missions reliably. Unfortunately, the failure of components is difficult to avoid due to the complexity of robot composition and the interference of the environment. Thus, improving the reliability of robots is a crucial problem. The hexapod robot has redundant degrees of freedom due to its multiple joints, making it possible to tolerate the failure of one leg. In this paper, the Fault-Tolerant Tripod (F-TT) gait dealing with the failure of one leg is researched. The Denavit–Hartenberg (D-H) method is exploited to establish a kinematic model for the hexapod robot, the Jacobian matrix is analyzed, and it is proved that the body can be controlled when three legs are supported. Then, an F-TT gait phase sequence planning method based on a stability margin is established, and a method to improve stability is proposed. The trajectory for the center of gravity (COG) and foot is studied. Finally, a simulation model and prototype robot experiments are developed, and the effectiveness of the proposed method is verified. Full article