This study evaluated the usability and effectiveness of robotic platforms working together with foresters in the wild on forest inventory tasks using LiDAR scanning. Emphasis was on the Universal Access principle, ensuring that robotic solutions are not only effective but also environmentally responsible and accessible for diverse users. Three robotic platforms were tested: Boston Dynamics Spot, AgileX Scout, and Bunker Mini. Spot's quadrupedal locomotion struggled in dense undergrowth, leading to frequent mobility failures and a System Usability Scale (SUS) score of 78 +/- 10. Its short, battery life and complex recovery processes further limited its suitability for forest operations without substantial modifications. In contrast, the wheeled AgileX Scout and tracked Bunker Mini demonstrated superior usability, each achieving a high SUS score of 88 +/- 5. However, environmental impact varied: Scout's wheeled design caused minimal disturbance, whereas Bunker Mini's tracks occasionally damaged young vegetation, highlighting the importance of gentle interaction with natural ecosystems in robotic forestry. All platforms enhanced worker safety, reduced physical effort, and improved LiDAR workflows by eliminating the need for human presence during scans. Additionally, the study engaged forest engineering students, equipping them with hands-on experience in emerging robotic technologies and fostering discussions on their responsible integration into forestry practices. This study lays a crucial foundation for the integration of Artificial Intelligence (AI) into forest robotics, enabling future advancements in autonomous perception, decision-making, and adaptive navigation. By systematically evaluating robotic platforms in real-world forest environments, this research provides valuable empirical data that will inform AI-driven enhancements, such as machine learning-based terrain adaptation, intelligent path planning, and autonomous fault recovery. Furthermore, the study holds high value for the international research community, serving as a benchmark for future developments in forestry robotics and AI applications. Moving forward, future research will build on these findings to explore adaptive remote operation, AI-powered terrain-aware navigation, and sustainable deployment strategies, ensuring that robotic solutions enhance both operational efficiency and ecological responsibility in forest management worldwide.

Soft wet grounds such as mud, sand, or forest soils, are difficult to navigate because it is hard to predict the response of the yielding ground and energy lost in deformation. In this article, we address the control of quadruped robots' static gait in deep mud. We present and compare six controller versions with increasing complexity that use a combination of a creeping gait, a foot-substrate interaction detection, a model-based center of mass positioning, and a leg speed monitoring, along with their experimental validation in a tank filled with mud, and demonstrations in natural environments. We implement and test the controllers on a Go1 quadruped robot and also compare the performance to the commercially available dynamic gait controller of Go1. While the commercially available controller was only sporadically able to traverse in 12 cm deep mud with a 0.35 water/solid matter ratio for a short time, all proposed controllers successfully traversed the test ground while using up to 4.42 times less energy. The results of this article can be used to deploy quadruped robots on soft wet grounds, so far inaccessible to legged robots.

Aerosols are an important factor leading to reduced visibility. In order to better comprehend the connection between visibility and aerosols, aerosol optical depth (AOD) and Angstrom exponent (AE) data from the Himawari-8 Advanced Himawari Imager (AHI) are used for validation in comparison with the data from the Aerosol Robotic Network (AERONET) observations in this paper, which amounted to 69,026 sets of data. The results indicate that the AOD of AHI is in good agreement with AERONET observations, but AE performs poorly. The correlation coefficients between the AOD of AHI and AERONET data increase with decreasing visibility and the root mean square error increase. The AE of AHI performs poorly in different visibility conditions. The conclusion drawn from further analysis of the correlation between aerosol products and meteorological factors is that the factor with the highest correlation with visibility. Mixed aerosols dominate at higher visibility and biomass burning/urban-industrial aerosols dominate at lower visibility. The visibility in a typical city (Beijing) has a strong negative correlation with AOD, a weak negative correlation with AE, and a strong correlation with aerosol radiative forcing. The reduction in visibility may be caused by the scattering and adsorption effects of aerosols. The results are important for the improvement and application of AHI aerosol products in regional pollution studies.

The sinkage of underwater landing robots deployed on loose seabed sediment over extended periods poses a significant challenge. Excessive sinkage can significantly reduce the locomotion performance of robots or even cause them to become trapped in the sediment. The study investigates the long-term sinkage behavior of underwater landing robots on seabed sediments using numerical simulations. Focusing on varying pressure source geometries and sediment mechanical properties, this research identifies distinct stages of sediment sinkage: transient, viscoelastic, and stable creep. A time-dependent pressure-sinkage model is established to predict sinkage behavior over extended durations, accounting for the effects of pressure magnitude, pressure source geometry, and sediment characteristics. Results demonstrate significant differences in sinkage depth between cylindrical and plate pressure sources, with maximum disparities reaching 158 mm under high-pressure conditions. The study further reveals that sediment parameters such as density, cohesion, and internal friction angle significantly influence sinkage, particularly in later stages, whereas loading rates affect initial but not long-term sinkage. The findings provide valuable insights for optimizing underwater landing robot designs and operational strategies, especially for long-term seabed deployments on complex sediment types. This research offers guidance for mitigating excessive sinkage risks and improving stability in underwater environments with varied sedimentary conditions.

The root-knot nematode (Meloidogyne spp.) is an obligate plant parasite and is one of the largest threats to the Australian sweetpotato industry, causing crop losses of up to 57% of marketable yield. In this study, two potential fungal biocontrol agents were encapsulated in alginate granules and their nematophagous activity was assessed in a laboratory-based microcosm experiment. Both species of fungi significantly reduced numbers of root-knot nematodes in red ferrosol soil. A greater reduction was observed in untreated field soil prior to introduction of root-knot nematodes and fungal biocontrol agents compared to soil that had been heat-sterilised. In a ten-week glasshouse experiment, no significant difference in the root-knot nematode populations in sweetpotato roots and soil was found between fungal biocontrol agent and control treatments. There was a trend towards an increase in the sweetpotato storage root weight and reduction in storage root damage in fungal biocontrol agent compared to control treatments, and both yield and damage levels were similar to those achieved from the use of chemical nematicide treatments. These results demonstrate the need for greater understanding of the interactions between soil biological populations and introduced nematophagous fungi if effective biocontrol is to be consistently achieved with these bioagents under field conditions.

Weed control in agricultural systems is of the utmost importance. Weeds reduce crop yields by up to 30% to 40%. Different methods are used to control weeds, such as manual, chemical, mechanical, and precision weed management. Weeds are managed more effectively by using the hand weeding method, which nevertheless falls short due to the unavailability of labor during peak periods and increasing labor wages. Generally, manual weeding tools have higher weeding efficiency (72% to 99%) but lower field capacity (0.001 to 0.033 hm(2)/h). Use of chemicals to control weeds is the most efficient and cost-effective strategy. Chemical weedicides have been used excessively and inappropriately, which has over time resulted in many issues with food and environmental damage. Mechanical weed control improves soil aeration, increases water retention capacity, slows weed growth, and has no negative effects on plants. Mechanical weed management techniques have been gaining importance recently. Automation in agriculture has significantly enhanced mechanization inputs for weed management. The development of precision weed management techniques offers an efficient way to control weeds, contributing to greater sustainability and improved agricultural productivity. Devices for agricultural automated navigation have been built on the rapid deployment of sensors, microcontrollers, and computing technologies into the field. The automated system saves time and reduces labor requirements and health risks associated with drudgery, all of which contribute to more effective farm operations. The new era of agriculture demands highly efficient and effective autonomous weed control techniques. Methods such as remote sensing, multispectral and hyperspectral imaging, and the use of robots or UAVs (drones) can significantly reduce labor requirements, enhance food production speed, maintain crop quality, address ecological imbalances, and ensure the precise application of agrochemicals. Weed monitoring is made more effective and safer for the environment through integrated weed management and UAVs. In the future, weed control by UAV or robot will be two of the key solutions because they do not pollute the environment or cause plant damage, nor do they compact the soil, because UAV sprays above the ground and robotic machines are lighter than tractor operated machines. This paper aims to review conventional, chemical, mechanical, and precision weed management methods.

The study of various celestial bodies is of great interest at the present time. Soil studies are being conducted. Vibrating robots could be possible tools for implementing the missions involving moving on the surface of celestial bodies. At the same time, such missions must be safe and sustainable. Such missions are very expensive. And they require high-quality modeling. The dynamics of a vibrating robot is investigated in this work. These structures can move on the surface of various celestial bodies, such as Mars, the Moon or asteroids. Various models can be used as a model of the contact interaction of bodies with a surface, in particular the AmontonCoulomb law of friction. This paper is aimed at studying a mechanical system consisting of a rigid body (outer body) placed on a horizontal rough plane and of an internal moving mass moving inside the outer body in a circle lying in a vertical plane, so that the radius vector of the point has a constant angular velocity. Based on the general properties of the solutions, possible periodic modes and their features depending on the parameters of the problem are considered. All qualitatively different solutions in this case are described.

Traditional robotic grippers encounter significant challenges when handling small objects in confined spaces, underscoring the need for innovative instruments with enhanced space efficiency and adaptability. Erodium cicutarium awns have evolved hygroresponsive helical deformation, efficiently driving seeds into soil crevices with limited space utilization. Drawing inspiration from this natural mechanism, we developed a biomimetic thin-walled actuator with water-responsive helical capabilities. It features a composite material structure comprising common engineering materials with low toxicity. Leveraging fused deposition modeling 3D printing technology and the composite impregnation process, the actuator's manufacturing process is streamlined and cost-effective, suitable for real-world applications. Then, a mathematical model is built to delineate the relationship between the biomimetic actuator's key structural parameters and deformation characteristics. The experimental results emphasize the actuator's compact dimension (0.26 mm thickness) and its capability to form a helical tube under 5 mm diameter within 60 s, demonstrating outstanding space efficiency. Moreover, helical characteristics and stiffness of the biomimetic actuators are configurable through precise modifications to the composite material structure. Consequently, it is capable of effectively grasping an object smaller than 3 mm. The innovative mechanism and design principles hold promise for advancing robotic technology, particularly in fields requiring high space efficiency and adaptability, such as fine tubing decongestion, underwater sampling, and medical endoscopic surgery.

The decreasing rural population and migration to urban areas for high-tech opportunities have weakened the agricultural labor force. While data technology has been adopted in protected agriculture, numerous challenges remain in field agriculture. In this study, we focus on one of the fundamental steps of field operations, i.e., ridge forming, specifically in unmanned agriculture. We compared the performance of a conventional tractor with an implement to that of a ridge-forming robot. The operation data were collected using an acquisition system, and a comparison between the results of both methods was conducted. Additionally, we analyzed the linearity of autonomous driving and the expenses associated with the selected operation. Our findings indicate that the developed robot for ridge forming caused less torque damage and achieved a more accurate target soil depth, with a linearity performance showing a distance error of only 0.267 m. Furthermore, it eliminated the need for hiring an operator and significantly reduced fuel consumption, which accounts for 50.81% of the operational expenses. These results suggest that field operations can be effectively replaced by autonomous systems, and further research on unmanned agriculture is warranted.

The success of weed control is critical for our food security. Non-chemical weed control is a promising technique in sustainable agriculture to ensure the food security. In this review, multiple directed energy weed control methods are reviewed with a specific focus on laser and optical radiation weed control. The mechanisms of the weed control in terms of adverse ablation, radiation thermal effects, and molecular-level damages are systematically reviewed. In particular, the underlying mathematical models determining the dose and response relationship of the weed control are also analyzed for a rigorous study of the physical law of the control process. Challenges of applying the techniques into practice are also illustrated to guide practical weed control applications.