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Fully-actuated unmanned aerial vehicles (UAVs) are a growing and promising field of research, which shows advantages for aerial physical interaction. The purpose of this paper is to construct a force sensor-denied control method for a fully-actuated hexarotor to conduct aerial interaction with accurate force exerted outward.

First, by extending single-dimension impedance model to the fully-actuated UAV model, an impedance controller is designed for compliant UAV pose/force control. Then, to estimate the interaction force between UAV end-effector and external environment accurately, combined with super-twisting theory, a nonlinear force observer is constructed. Finally, based on impedance controller and estimated force from observer, an interaction force regulation method is proposed.

The presented nonlinear observer-based impedance control approach is validated in both simulation and environments, in which the authors try to use a fully-actuated hexarotor to accomplish the task of aerial physical interaction finding that a specified force is able to be exerted to environment without any information from force sensors.

A solution of aerial physical interaction for UAV system enabling accurate force exerted outward without any force sensors is proposed in this paper.

This paper introduces control strategy to enhance the performance of a novel quadrotor unmanned aerial vehicle designed for medical payload delivery. The aim is to achieve precise control and stability when carrying and releasing payloads, which alter the quadrotor’s mass and inertia characteristics.

The equations of motion specific to the payload-carrying quadrotor are derived. A feedforward-proportional-integral-derivative (FF-PID) control strategy is then proposed to address the dynamic changes during payload release. The PID components use propeller speed/orientation information for stability. FF terms based on derivatives of desired position/orientation variables enable adaptation to real-time mass fluctuations.

Extensive simulations, encompassing various fault scenarios, substantiate the effectiveness of the FF-PID approach. Notably, our findings demonstrate superior performance in maintaining altitude precision and stability during critical phases such as takeoff, payload release and landing. Graphical representations of thrust and mass dynamics distinctly illustrate the payload release event. In contrast to the linear quadratic regulator (LQR) and conventional PID control, which encountered difficulties during the payload release process, our approach proves its robustness and reliability.

This study, primarily based on simulations, demands validation through real-world testing in diverse conditions. Uncertainties in dynamic parameters, external factors and the applicability of the proposed approach to other quadrotor configurations require further investigation. Additionally, this research focuses on controlled payload release, leaving unexplored the challenges posed by unforeseen scenarios or disturbances. Hence, adaptability and fault tolerance necessitate further exploration. While our work presents a promising approach, practical implementation, adaptability and resilience to unexpected events are vital considerations for future research in the field of autonomous aerial medical deliveries.

The proposed control strategy promises enhanced efficiency, reliability and adaptability for autonomous aerial medical deliveries in critical scenarios.

The innovative control strategy introduced in this study holds the potential to significantly impact society by enhancing the reliability and adaptability of autonomous aerial medical deliveries. This could lead to faster and more efficient delivery of life-saving supplies to remote or disaster-affected areas, ultimately saving lives and reducing suffering. Moreover, the technology’s adaptability may have broader applications in fields like disaster relief, search and rescue missions, and industrial cargo transport. However, its successful integration into society will require careful regulation, privacy safeguards and ethical considerations to ensure responsible and safe deployment while addressing potential concerns related to noise pollution and privacy intrusion.

While PID control of quadrotors is extensively studied, payload release dynamics have been overlooked. This research studies integration of FF control to enable PID adaptation for a novel payload delivery application.

Construction is a risky industry. Therefore, organizations are seeking ways towards improving their safety performance. Among these, the integration of technology into health and safety leads to enhanced safety performance. Considering the benefits observed in using technology in safety, this study aims to explore digital technologies' use and potential benefits in construction health and safety.

An extensive bibliometrics analysis was conducted to reveal which technologies are at the forefront of others and how these technologies are used in safety operations. The study used two different databases, Web of Science (WoS) and Scopus, to scan the literature in a systemic way.

The systemic analysis of several studies showed that the digital technologies use in construction are still a niche theme and need more assessment. The study provided that sensors and wireless technology are of utmost importance in terms of construction safety. Moreover, the study revealed that artificial intelligence, machine learning, building information modeling (BIM), sensors and wireless technologies are trending technologies compared to unmanned aerial vehicles, serious games and the Internet of things. On the other hand, the study provided that the technologies are even more effective with integrated use like in the case of BIM and sensors or unmanned aerial vehicles. It was observed that the use of these technologies varies with respect to studies conducted in different countries. The study further revealed that the studies conducted on this topic are mostly published in some selected journals and international collaboration efforts in terms of researching the topic have been observed.

This study provides an extensive analysis of WoS and Scopus databases and an in-depth review of the use of digital technologies in construction safety. The review consists of the most recent studies showing the benefits of using such technologies and showing the usage on a systemic level from which both scientists and practitioners can benefit to devise new strategies in technology usage.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

This study aims to discuss the simultaneous longitudinal and lateral flight control of the octorotor, a rotary wing unmanned aerial vehicle (UAV), for the first time under the effect of morphing and to improve autonomous flight performance.

This study aims to design and control the octorotor flight control system with stochastic optimal tuning under morphnig effect. For this purpose, models of different arm lengths of the octorotor were drawn in the Solidworks program. The morphing was carried out by simultaneously lengthening or shortening the arm lengths of the octorotor. The morphing rate was estimated by using simultaneous perturbation stochastic approximation (SPSA). The stochastic gradient descent algorithm, which is frequently used in machine learning, was used to estimate the changing moments of inertia with the change of arm lengths. The proportional integral derivative (PID) controller has been preferred as an octorotor control algorithm because of its simplicity of structure. The PID gains required to control both longitudinal and lateral flight were also estimated with SPSA.

With SPSA, three longitudinal flight PID gains, three lateral flight PID gains and one morphing ratio were estimated. PID gains remained within the limits set for SPSA, giving satisfactory results. In addition, the cost index created was 93% successful. The gradient descent algorithm used for the moment of inertia estimation achieved the optimum result in 1,570 iterations. However, in the simulations made with the obtained data, longitudinal and lateral flight was successfully carried out.

Octorotor longitudinal and lateral flight control was performed quickly and effectively with the proposed method. In addition, the desired parameters were obtained with the optimization methods used, and the longitudinal and lateral flight of the octorotor was successfully carried out in the desired trajectory.

Photogrammetry enables scientists and engineers to make accurate and precise measurements from optical images and other patterns of reflected electromagnetic energy. Photogrammetry is taught in surveying, geomatics and similar academic programs. For a long time, it has been observed that there is a lack of diversity and underrepresentation of different groups in the surveying and geomatics workforces for various reasons. Diversity fosters more innovative environments, helps employees be more engaged and boosts productivity rates. Although efforts are being made to solve this problem, most attempts did not significantly improve the diversity issues in this field. To address this problem, we designed a new curriculum for a photogrammetry course, which integrates entrepreneurial mindset (EM), bio-inspired design and Science, Technology, Engineering, Arts and Mathematics (STEAM) into the photogrammetry course for this study.

In this study, the participatory action research method, Photovoice, was used to gather data. Students were asked to respond to photovoice and metacognitive reflection prompts to understand student perceptions about the importance of Unmanned Aerial Vehicles (UAVs) in photogrammetric mapping. Students were required to respond to each prompt with three pictures and a narrative. These reflections were analyzed using thematic analysis.

The analysis of the photovoice and metacognitive reflections resulted in six themes: promoting digital literacy, promoting job readiness and awareness, improving perceived learning outcomes, increasing interest in pursuing careers in surveying/geomatics, encouraging learner engagement and increasing awareness of the role of art in map making.

This is the first study conducted at our Hispanic Serving Institution, which specifically designed a curriculum integrating EM, bio-inspired design and STEAM concepts to address diversity issues in surveying and geomatics engineering disciplines.

The purpose of this study is to investigate the effects of propeller thrust with two different duct configurations. Propellers in a quadcopter play an indispensable role in generating the necessary thrust and torque to keep the drone flying and manoeuvring. Based on the specific purpose of the unmanned aerial vehicle, both the altitude and attitude can be varied by the amount of thrust produced.

This paper deals with the generation of three numerical models such as plain rotor, rotor with fixed duct and rotor with rotating duct and the comparison of their amount of generated thrust. The plain rotor numerical analysis was compared with the experimental results. The rotor taken for the analysis was 15 mm*5.5 mm TAROT 650. Thrust was measured for all models at four different angular speeds, such as 2,500 rpm, 4,000 rpm, 5,500 rpm and 7,000 rpm.

Due to the suction pressure gradient on the duct inlet surface, the additional amount of lift is produced, and it is the best way of increasing propulsion efficiency and its aerodynamic performance as it reduces the tip loss at the tip of the propeller. The turbulence model taken for the numerical analysis was k−ε.

The rotating duct is expected to provide additional thrust by the increased upward force due to the rotation of duct. The rotating duct produced the optimal results between the plain model and ducted model. At the highest speed of 7,000 rpm, the ducted propeller produced 24.97 N, and the rotating duct propeller produced 23.89 N, whereas the plain propeller produced 23 N thrust. Nearly 8.6% of the thrust improvement is observed in duct and 3.87% in rotating duct.

Military and unmanned aerial vehicles (UAV) applications like rocket motor casings, missile covers and ship hulls use components that are made of maraging steel. Maraging steel has properties that are superior to other metals, making it more suitable for the fabrication of such components. A grey relational analysis (GRA) that is based on the Taguchi method has been utilised in the current study to optimise a laser beam welding (LBW) process. Further aspects such as GRA's optimum ranges and percentage contributions were also estimated.

A Taguchi L16 orthogonal array is utilised to design and conduct the experiments. Laser power (LP), welding speed (WS) and focal position (FP) are the three parameters are chosen for the process of welding. The output responses are the upper width of the heat-affected zone (HAZup), the upper width of the fusion zone (FZup) and the depth of penetration (DOP). The effect of the above key parameters on the responses was examined using an analysis of variance (ANOVA).

The results of ANOVA reveal that the parameter that has the most influence on the overall grey relational grade (GRG) is the FP. Finally, metallographic characterisation and a microstructural analysis are conducted on the weld bead geometry to demarcate the zone of HAZ and fusion zone (FZ).

As the most important criteria for LBW of maraging steels is the provision of higher DOP, higher FZ width and lower heat-affected zone, the study intended to prove the applicability of GRA technique in solving multi-objective optimisation problems in applications like defence and unmanned systems.

The present paper aims to address challenges associated with path planning and obstacle avoidance in mobile robotics. It introduces a pioneering solution called the Bi-directional Adaptive Enhanced A* (BAEA*) algorithm, which uses a new bidirectional search strategy. This approach facilitates simultaneous exploration from both the starting and target nodes and improves the efficiency and effectiveness of the algorithm in navigation environments. By using the heuristic knowledge A*, the algorithm avoids unproductive blind exploration, helps to obtain more efficient data for identifying optimal solutions. The simulation results demonstrate the superior performance of the BAEA* algorithm in achieving rapid convergence towards an optimal action strategy compared to existing methods.

The paper adopts a careful design focusing on the development and evaluation of the BAEA* for mobile robot path planning, based on the reference [18]. The algorithm has remarkable adaptability to dynamically changing environments and ensures robust navigation in the context of environmental changes. Its scale further enhances its applicability in large and complex environments, which means it has flexibility for various practical applications. The rigorous evaluation of our proposed BAEA* algorithm with the Bidirectional adaptive A* (BAA*) algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm. The BAEA* algorithm consistently outperforms BAA*, demonstrating its ability to plan shorter and more stable paths and achieve higher success rates in all environments.

The paper adopts a careful design focusing on the development and evaluation of the BAEA* for mobile robot path planning, based on the reference [18]. The algorithm has remarkable adaptability to dynamically changing environments and ensures robust navigation in the context of environmental changes. Its scale further enhances its applicability in large and complex environments, which means it has flexibility for various practical applications. The rigorous evaluation of our proposed BAEA* algorithm with the Bi-directional adaptive A* (BAA*) algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm.

The rigorous evaluation of our proposed BAEA* algorithm with the BAA* algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm. The BAEA* algorithm consistently outperforms BAA*, demonstrating its ability to plan shorter and more stable paths and achieve higher success rates in all environments.

The originality of this paper lies in the introduction of the bidirectional adaptive enhancing A* algorithm (BAEA*) as a novel solution for path planning for mobile robots. This algorithm is characterized by its unique characteristics that distinguish it from others in this field. First, BAEA* uses a unique bidirectional search strategy, allowing to explore the same path from both the initial node and the target node. This approach significantly improves efficiency by quickly converging to the best paths and using A* heuristic knowledge. In particular, the algorithm shows remarkable capabilities to quickly recognize shorter and more stable paths while ensuring higher success rates, which is an important feature for time-sensitive applications. In addition, BAEA* shows adaptability and robustness in dynamically changing environments, not only avoiding obstacles but also respecting various constraints, ensuring safe path selection. Its scale further increases its versatility by seamlessly applying it to extensive and complex environments, making it a versatile solution for a wide range of practical applications. The rigorous assessment against established algorithms such as BAA* consistently shows the superior performance of BAEA* in planning shorter paths, achieving higher success rates in different environments and cementing its importance in complex and challenging environments. This originality marks BAEA* as a pioneering contribution, increasing the efficiency, adaptability and applicability of mobile robot path planning methods.

Using building information modelling (BIM) technology, a conventional structure in this study was converted into a green building to measure its energy usage and CO2 emissions.

Digital images of the existing building conditions were captured using unmanned aerial vehicle (UAV), and were fed into Meshroom to generate the building’s geometry for 3D parametric model development. The model for the existing conventional building was created and converted to an energy model and exported to gbXML in Autodesk Revit for a whole building analysis which was carried out in the Green Building Studio (GBS). In the GBS, the conventional building was retrofitted into a green building to explore their energy consumption and CO2 emission.

By comparing the green building model to the conventional building model, the research found that the green building model saved 25% more energy while emitting 46.8% less CO2.

The study concluded that green building reduces energy consumption, thereby reducing the emission of CO2 into the environment. It is recommended that buildings should be simulated at the design stage to know their energy consumption and carbon emission performance before construction.

Occupant satisfaction, operation cost and environmental safety are essential for sustainable or green buildings. Green buildings increase the standard of living and enhance indoor air quality.

This investigation aided in a pool of information on how to use BIM methodology to retrofit existing conventional buildings into green buildings, showing how green buildings save the environment as compared to conventional buildings.