Search Results (70)

Unmanned Aerial Vehicles (UAVs) are known to have limited payloads, which challenges their widespread use in transporting heavy goods. Meanwhile, collaboration between multiple UAVs in performing such a task may be a promising solution. To address the issues associated with the simultaneous use of UAVs, this paper presents a formation control system for transporting a payload suspended via a cable using two UAVs. The control structure is based on a layered scheme that combines a null-space-based kinematic controller with a PID controller associated with each UAV (quadcopters) with a neural correction system. The null-space supervisor controller is designed to generate the desired velocity for the UAV system to maintain formation. This proposal aims to avoid obstacles, balance the weight distribution across each vehicle, and also reduce the payload trajectory tracking error. The PID controller associated with the neural correction system receives these desired speeds and performs dynamic compensation, taking into account parametric uncertainties and dynamic disturbances caused by the movement of the payload coupled to the UAV systems. The stability analysis of the entire control system is performed using Lyapunov theory. Detailed dynamic models of each UAV in the system, the flexible cables, and the payload are presented in a realistic scenario. Finally, numerical simulations demonstrate the good performance of the UAV system control in formation. Full article

Tethered unmanned aerial vehicles (UAVs) operating in terrestrial environments face critical safety challenges from power cable breaks, yet existing solutions—including fiber optic sensing (cost > USD 20,000) and impedance analysis (35% payload increase)—suffer from high cost or heavy weight. This study proposes a dual innovation: a real-time break detection method and a low-cost multi-core parallel sensing system design based on ACS712 Hall sensors, achieving high detection accuracy (100% with zero false positives in tests). Unlike conventional techniques, the approach leverages current differential (ΔI) monitoring across parallel cores, triggering alarms when ΔI exceeds I_rate/2 (e.g., 0.3 A for 0.6 A rated current), corresponding to a voltage deviation ≥ 110 mV (normal baseline ≤ 3 mV). The core innovation lies in the integrated sensing system design: by optimizing the parallel deployment of ACS712 sensors and LMV324-based differential circuits, the solution reduces hardware cost to USD 3 (99.99% lower than fiber optic systems), payload by 18%, and power consumption by 23% compared to traditional methods. Post-fault cable temperatures remain ≤56 °C, ensuring safety margins. The 4-core architecture enhances mean time between failures (MTBF) by 83% over traditional systems, establishing a new paradigm for low-cost, high-reliability sensing systems in terrestrial tethered UAV cable health monitoring. Preliminary theoretical analysis suggests potential extensibility to underwater scenarios with further environmental hardening. Full article

This study investigates the cooperative transport of a cable-suspended payload by two multirotor unmanned aerial vehicles (UAVs). A compact nonlinear control law that allows to simultaneously (i) track a slow reference trajectory, (ii) hold a prescribed inter-vehicle geometry, and (iii) actively damp load swing is developed. The model treats the two aerial robots and the payload as three point masses connected by linear-elastic cables, and the controller is obtained through a Newton–Euler formulation. A singular-perturbation analysis shows that, under modest gain–separation conditions, the closed-loop system is locally exponentially stable: fast dynamics govern formation holding and swing suppression, while slow dynamics takes into account trajectory tracking. Validation is performed in a realistic simulation scenario that includes six-degree-of-freedom rigid-body vehicles, Blade-Element theory rotor models, and sensor noise. Compared to an off-the-shelf, baseline controller, the proposed method significantly improves flying qualities while minimizing hazardous payload oscillations. Owing to its limited parameter set and the absence of heavy optimization, the approach is easy to tune and well suited for real-time implementation on resource-limited UAVs. Full article

Inspection, maintenance, and repair (IMR) operations on underwater infrastructure remain costly and time-intensive because fully teleoperated remote operated vehicle s(ROVs) lack the range and dexterity necessary for precise cooperative underwater manipulation, and the alternative of using professional divers is ruled out due to the risk involved. This work presents and experimentally validates an autonomous, dual-I-AUV (Intervention–Autonomous Underwater Vehicle) system capable of assembling rigid pipeline segments through coordinated actions in a confined underwater workspace. The first I-AUV is a Girona 500 (4-DoF vehicle motion, pitch and roll stable) fitted with multiple payload cameras and a 6-DoF Reach Bravo 7 arm, giving the vehicle 10 total DoF. The second I-AUV is a BlueROV2 Heavy equipped with a Reach Alpha 5 arm, likewise yielding 10 DoF. The workflow comprises (i) detection and grasping of a coupler pipe section, (ii) synchronized teleoperation to an assembly start pose, and (iii) assembly using a kinematic controller that exploits the Girona 500’s full 10 DoF, while the BlueROV2 holds position and orientation to stabilize the workspace. Validation took place in a 12 m × 8 m × 5 m water tank. Results show that the paired I-AUVs can autonomously perform precision pipeline assembly in real water conditions, representing a significant step toward fully automated subsea construction and maintenance. Full article

The increasing presence of high-rise buildings with curved and convex facades poses significant challenges for facade-cleaning robots, particularly in terms of mobility and anchoring. To address this, we propose a rope-riding mobile anchor (RMA) system capable of repositioning the anchor point of a cleaning robot on convex building surfaces. The RMA travels horizontally along a roof-mounted nylon rope using caterpillar tracks with U-shaped grooves, and employs a four-bar linkage mechanism to fix its position securely by increasing rope contact friction. This structural principle was selected for its simplicity, stability under heavy loads, and efficient actuation. Experimental results show that the RMA can support a payload of 50.5 kg without slippage under tensions up to 495.24 N, and contributes to reducing the power consumption of the cleaning robot during operation. These findings demonstrate the RMA’s effectiveness in extending the robot’s working range and enhancing safety and stability in facade-cleaning tasks on complex curved surfaces. Full article

Hydraulic actuated legged robots display bright prospects and significant research value in areas such as unmanned area surveying, disaster rescue, military fields, and other scenarios owing to their excellent bionic characteristics, particularly their heavy payload capabilities and high power density. To realize the all-terrain adaptation locomotion of the hydraulic hexapod robot (HHR) with a heavy payload, one alternative control framework is position–posture control based on joint position control. As the foundation for the steady locomotion of HHRs, it is imperative to realize high-precision joint position control to improve the robustness under external disturbances during the walking process and to complete the attitude control task. To address the above issues, this paper proposes a sliding mode repetitive control based on the unknown dynamics estimator (SMRC + UDE) for the knee and hip joints of the HHR with a two-stage supply pressure hydraulic system (TSS). The effectiveness of the SMRC + UDE method is verified using a simulation environment and the ZJUHEX01 prototype experimental platform, and it is compared with the results for PID and adaptive robust sliding mode control (ARSMC). The results show that SMRC + UDE may be more suitable for our HHR, considering both the control performance and efficiency factors. Full article

Utilizing deep learning models to detect malicious anomalies within the traffic of application layer J1939 protocol networks, found on heavy-duty commercial vehicles, is becoming a critical area of research in platform protection. At the physical layer, the controller area network (CAN) bus is the backbone network for most vehicles. The CAN bus is highly efficient and dependable, which makes it a suitable networking solution for automobiles where reaction time and speed are of the essence due to safety considerations. Much recent research has been conducted on securing the CAN bus explicitly; however, the importance of protecting the J1939 protocol is becoming apparent. Our research utilizes long short-term memory models to predict the next binary data sequence of a J1939 packet. Our primary objective is to compare the performance of our J1939 detection system trained on data sub-fields against a published CAN system trained on the full data payload. We conducted a series of experiments to evaluate both detection systems by utilizing a simulated attack representation to generate anomalies. We show that both detection systems outperform one another on a case-by-case basis and determine that there is a clear requirement for a multifaceted security approach for vehicular networks. Full article

Due to the limitations of current battery technologies—such as lower energy density and high cost compared to fossil fuels—electric vehicles (EVs) face constraints in applications requiring extended range or heavy payloads, such as refuse trucks. As a midterm solution, hybrid electric vehicles (HEVs) combine internal combustion engines (ICEs) and electric powertrains to enable flexible energy usage, particularly in urban duty cycles characterized by frequent stopping and idling. This study introduces a model-based energy management strategy using the Equivalent Consumption Minimization Strategy (ECMS), tailored for a retrofitted series hybrid refuse truck. A conventional ISUZU NPR 10 truck was instrumented to collect real-world driving and operational data, which guided the development of a vehicle-specific ECMS controller. The proposed strategy was evaluated over five driving cycles—including both standardized and measured urban scenarios—under varying load conditions: Tare Mass (TM) and Gross Vehicle Mass (GVM). Compared with a rule-based control approach, ECMS demonstrated up to 14% improvement in driving range and significant reductions in exhaust gas emissions (CO, NO_x, and CO₂). The inclusion of auxiliary load modeling further enhances the realism of the simulation results. These findings validate ECMS as a viable strategy for optimizing fuel economy and reducing emissions in hybrid refuse truck applications. Full article

Heavy-duty vehicles (HDVs), such as buses and commercial trucks, display unique dynamic characteristics due to their high mass and specific actuator properties. These factors make HDVs particularly sensitive to changes in vehicle load and road gradient, which significantly affect their longitudinal control performance. In other words, such variations present considerable challenges in maintaining stable and efficient longitudinal control of HDVs. To address these challenges, this study proposes a model reference adaptive control (MRAC) framework explicitly designed for HDVs. The control system utilizes a state predictor to mitigate actuator load problems caused by high-frequency components in the adaptive control input. In addition, when input constraints are present, the reference model is modified using the μ-modification technique. The system satisfies Lyapunov stability conditions and ensures stable longitudinal control performance across a range of driving conditions. The proposed closed-loop longitudinal control system was evaluated by implementing the controller using the vehicle dynamics simulation software IPG TruckMaker 12.0.1 and integrated with MATLAB/Simulink R2022b. The test scenarios included repetitive speed change maneuvers, which accounted for uncertainties such as road gradients, headwinds, and vehicle load conditions. The simulation results show that the control system not only effectively suppresses disturbances but also enables stable longitudinal speed tracking by considering actuator load and constraints, outperforming conventional MRAC. These results suggest that the proposed closed-loop longitudinal control system can be effectively applied to HDVs. The findings suggest that the proposed closed-loop longitudinal control system can be effectively applied to HDVs, ensuring improved stability and performance under real-world driving conditions. Full article

There is an urgent need for a method of evaluating the real energy performance of vehicles that eliminates the effects of external conditions (topography, altitude, and road conditions) and human factors (driving styles), especially in the case of heavy-duty vehicles. Governmental authorities require results on the energy performance of vehicles to develop strategies that result in reductions in greenhouse gas emissions, while fleet managers require results regarding the energy efficiency of existing vehicle technologies to select the technologies that minimize energy consumption and, therefore, operational costs. Aiming to address this need, we propose a method for evaluating the global energy efficiency of road vehicles by monitoring at 1 Hz the operational variables of a vehicle under normal conditions of use for a long time. The variables monitored are engine RPM and vehicle location, speed, payload, and energy consumption. This method was verified using 49 vehicles, representing 23 vehicle technologies. These vehicles varied in size (light duty and heavy duty), application (cars, buses, and freight), energy sources (gasoline, diesel, and electric), and operational conditions (Chile, Ecuador, Colombia, and México). Testing was conducted across various altitudes (0–3600 masl) and topographies (flat and mountainous regions). The results showed that the energy efficiencies for gasoline-fueled light-duty vehicles ranged from 17 to 30%, those for diesel-fueled heavy-duty vehicles ranged from 25 to 42%, and those for electric heavy-duty vehicles (HDVs) ranged from 70 to 80%. Full article

Dynamic response characteristics of the passive heave compensator with auxiliary gas bottles are investigated in this paper. A mathematical model of the passive heave compensator is developed which includes mechanics, hydraulics and pneumatics. The key innovation of the proposed model is that the thermodynamic model of gas exchange between the piston accumulator and the gas bottles is derived and discussed. Meanwhile, a one-dimensional model of the pipeline resistance effect is established to calculate the pressure drop across the oil pipeline. The proposed model is used to evaluate the different design parameters of the passive heave compensator for heavy lifting cranes. A study was conducted to investigate the influence of the design parameters on the effectiveness of the passive compensator to reduce the payload displacement. The simulation results indicated that substantial improvement may be possible by careful design parameter selection and optimization. Full article

Equipping satellites with a series of high-precision frequency references is essential; however, even advanced active hydrogen masers can often be too heavy and expensive for the current satellite payload constraints. Moreover, in geostationary Earth-orbit communication satellites lacking atomic clocks, onboard oscillators can degrade the performance of time–frequency transmission methods. To address these challenges, this study proposes a novel phase-locked transponder that leverages Einstein’s synchronization theory and real-time carrier-phase compensation to improve the transmission performance of satellite frequency transfer systems while mitigating the noise from onboard satellite oscillators. Notably, this requires only simple modifications to the existing transponder structure. By replicating the high-precision atomic frequency standards from ground stations to satellites, the proposed system achieves enhanced frequency synchronization without additional onboard clocks. The feasibility of the satellite-to-ground link was validated through both a theoretical analysis and an experimental verification. Specifically, ground experiments demonstrated a reproducibility of 6.33 ps (1σ) over a 24 h period, with a long-term frequency stability of 3.36 × 10⁻¹⁶ at an average time of 10,000 s under dynamic conditions, showcasing the potential of this approach for advanced frequency synchronization. This paper presents a cost-effective and scalable solution for enhancing frequency synchronization in geostationary satellites, improving communication reliability, supporting advanced scientific and navigational applications, and enabling the development of high-precision, space-air-ground integrated time–frequency synchronization networks. Full article

The transport sector is responsible for nearly a quarter of global CO₂ emissions annually, underscoring the urgent need for cleaner, more sustainable alternatives such as electric vehicles (EVs). However, the electrification of heavy goods vehicles (HGVs) has been slow due to the substantial power and battery capacity required to match the large payloads and extended operational ranges. This study addresses the research gap in battery pack design for commercial HGVs by investigating the electrical and thermal behaviour of a novel battery pack configuration using an electro-thermal model based on the equivalent circuit model (ECM). Through computationally efficient 1D modelling, this study evaluates critical factors such as cycle ageing, state of charge (SoC), and their impact on the battery’s range, initially estimated at 285 km. The findings of this study suggest that optimal cooling system parameters, including a flow rate of 18 LPM (litres per minute) and actively controlling the inlet temperature within ±7.8 °C, significantly enhance thermal performance and stability. This comprehensive electro-thermal assessment and the advanced cooling strategy set this work apart from previous studies centred on smaller EV applications. The findings provide a foundation for future research into battery thermal management system (BTMS) design and optimised charging strategies, both of which are essential for accelerating the industrial deployment of electrified HGVs. Full article

In this paper, the design of a driving mechanism for a heavy-duty collaborative robot (cobot) capable of lifting payloads up to 20 kg is presented. This study focuses on an articulated robot utilizing a water-based Electro-Hydraulic Actuator (EHA). The Denavit–Hartenberg (D–H) representation was employed to relate the rotational angles and the end-effector’s location, facilitating the design of the actuators. The maximum required torques for joints 2 and 3, responsible for lifting for 12 s, were calculated under quasi-static and dynamic loading conditions. The results showed that the maximum required torques were 126.67 Nm and 58.86 Nm for joint 2 and 3, respectively. The maximum torque for joint 2 occurs when the pitch links are fully extended, whereas the maximum torque for joint 3 occurs when the third link is parallel to the ground. The torques, due to the inertia and Coriolis dynamic terms, were also calculated and found to be lower than those required for the gravitational term. Various maneuvering scenarios, along with Ansys Motion simulation, were analyzed for the verification of the results. Based on the calculated maximum torques, the linear actuators of the EHA were designed. The heavy-duty cobot can be built with the developed actuator proposed in this paper. The total weight of the entire frame was measured to be 14.59 kg, resulting in a high Payload/Weight (P/W) ratio of 1.37. In conclusion, the robot was made lighter and can operate more efficiently, particularly for heavy loads up to 20 kg. Full article

Particle radiation on the Moon is influenced by a combination of galactic cosmic rays, high-energy solar particles, and secondary particles interacting on the lunar surface. When China’s Chang’e-7 lander lands at the Moon’s South Pole, it will encounter this complex radiation environment. Therefore, a payload detection technology was developed to comprehensively measure the energy spectrum, direction, and radiation effects of medium- and high-energy charged particles on the lunar surface. During the ground development phase, the payload performance was tested against the design specifications. The verification results indicate that the energy measurement ranges are 30 keV to 300 MeV for protons, 30 keV to 12 MeV for electrons, and 8 to 400 MeV/n for heavy ions. The energy resolution is 10.81% for 200 keV electrons of the system facing the lunar surface; the dose rate measurement sensitivity is 7.48 µrad(Si)/h; and the LET spectrum measurement range extends from 0.001 to 37.014 MeV/(mg/cm²). These comprehensive measurements are instrumental in establishing a lunar surface particle radiation model, enhancing the understanding of the lunar radiation environment, and supporting human lunar activities. Full article