Research on path planning for clear aligner flexible manufacturing.

In recent years, clear aligner can enhance individual appearance with dental defects, so it used more and more widely. However, in manufacturing process, there are still some problems, such as low degree of automation and high equipment cost. The problem of coordinate system mismatch between gingival curve point cloud and dental CAD model is faced to. The PCA-ICP registration algorithm is proposed, which includes coarse match algorithm and improve-ICP registration algorithm. The principal component analysis (PCA) based method can roughly find the posture relationship between the two point clouds. Using z-level dynamic hierarchical, the ICP registration can accurately find the posture between these two clouds. The final registration maximum distance error is 0.03 mm, which is smaller than robot machining error. Secondly, the clear aligner machining process is conducted to verify the registration effectiveness. Before machining, the path is generated based on the well registered gingival curve. After full registration, the tool path is calculated by establishing a local coordinate system between the workpiece and the tool to avoid interference. This path is calculated and generated as an executable program for ABB industrial robots. Finally, the robot was used for flexible cutting of clear aligners and was able to extract products, ensuring the effectiveness of the proposed research. This method can effectively solve the limitations of traditional milling path planning under such complex conditions.

A review of robot-assisted ultrasound examination: Systems and technology.

BACKGROUND: At present, the number and overall level of ultrasound (US) doctors cannot meet the medical needs, and the medical ultrasound robots will largely solve the shortage of medical resources. METHODS: According to the degree of automation, the handheld, semi-automatic and automatic ultrasound examination robot systems are summarised. Ultrasound scanning path planning and robot control are the keys to ensure that the robot systems can obtain high-quality images. Therefore, the ultrasound scanning path planning and control methods are summarised. The research progress and future trends are discussed. RESULTS: A variety of ultrasound robot systems have been applied to various medical works. With the continuous improvement of automation, the systems provide high-quality ultrasound images and image guidance for clinicians. CONCLUSION: Although the development of medical ultrasound robot still faces challenges, with the continuous progress of robot technology and communication technology, medical ultrasound robot will have great development potential and broad application space.

Factors associated with intention of HIV testing among Asian American men: a path analysis.

Research has pointed to myriad cultural and socio-psychological factors associated with HIV testing, such as acculturation, social norms about HIV testing, masculinity, homonegativity, and constructs from the Theory of Planned Behavior. However, the interrelationships of these factors on the intentions of HIV testing among the population of Asian American men remains unknown. A dataset of 425 Asian American men in the U.S., collected online with convenience sampling method during 2020-2021, was analyzed to test a conceptual framework that aimed to fill this gap. Results from a path model with two endogenous variables (homonegativity and HIV testing intention) indicated that perceived social norms about HIV testing, attitude about HIV testing, and perceived HIV risk had directandindirect relationships with the intentions of HIV testing in the study population. However, social norms about HIV testing and perceived HIV risk showed stronger direct effects (standardized estimates = 0.37 and 0.34, respectively, p-value < 0.001). Additionally, we found that the relationships of these factors with HIV testing intention were also mediated by homonegativity. Findings from this study advance our understanding of pathways of associations between a host of cultural and socio-psychological factors with HIV testing intention among an understudied population - Asian American men. Our results will help inform the development of future intervention programs to increase HIV testing in this population.

Incorporating vertical movement of fishes in habitat use models.

Fish telemetry studies now routinely collect positional and depth data, yet analytical approaches that integrate three-dimensional data are limited. Here we apply the potential path volume (PPV) model, a method previously developed to estimate habitat volume based on rates of avian movement, to free-swimming fish. Using a telemetry dataset of white sucker (Catastomus commersonii) from Turkey Lake (Ontario, Canada), we evaluated the effects of the number of spatial positions and different methods of selecting swim speed (vswim), a key parameter for PPV models, on habitat volume estimates. We subsequently compared habitat volume estimates and habitat overlap among white sucker pairs from the PPV models to those calculated using kernel utilization distribution-based approaches. The number of spatial positions in the PPV model had a significant effect on habitat volume estimates, whereas the magnitude of the vswim parameter or its specificity (constant value vs. fish-season specific parameter values) did not affect habitat volume estimates. The PPV method resulted in larger habitat volume estimates and greater habitat overlap estimates among fish pairs relative to those obtained from a three-dimensional kernel utilization distribution method. The PPV model is a useful analytical tool that, by incorporating potential animal movement into habitat use evaluations, can help answer key ecological questions and provide insight into fish space use in a wide range of conservation and management applications.

Low-carbon development path based on carbon emission accounting and carbon emission performance evaluation: a case study of Chinese coal production enterprises.

Carbon emission accounting is the basic premise of effective carbon emission reduction and management. This study aimed to establish the carbon emission model and performance evaluation framework of coal mine production enterprises and clarify the low-carbon development path of enterprises. In this study, we took a typical coal production enterprise (K enterprise) in the Shanxi province of China as the research object. We also estimated the carbon emissions of the enterprise mainly according to the Chinese Carbon Emission Accounting Standard (GB/T 32151.11-2018). The triangular model was used to construct the carbon performance evaluation framework. On this basis, we suggested the enterprise's low-carbon development path. The results showed that (1) the carbon emission of K enterprise in 2021 was 36,875.38 tCO2eq; the carbon emission intensity of each ton of coal produced was 0.089 tCO2eq. The critical carbon emissions were electricity consumption and methane fugitive emissions during production. (2) The evaluation indicators for carbon emission performance revealed an imbalance in K enterprise's economic, energy, and environmental development in 2021. The work on energy saving and consumption reduction was relatively weak. (3) Countermeasures for low-carbon development, including a carbon emission ledger, were proposed based on carbon emission accounting and performance evaluation results. This study can help typical underground coal production enterprises in Shanxi province obtain more accurate carbon emission data, providing practical guidance and reference for the same underground coal production enterprises to improve the carbon emission control effect.

Yixin-Fumai granules modulate autophagy through the PI3K/AKT/FOXO pathway and lead to amelioration of aging mice with sick sinus syndrome.

OBJECTIVE: By employing network pharmacology alongside molecular docking techniques, we can delve into the intricate workings of Yixin-Fumai granules (YXFMs) and their impact on sick sinus syndrome (SSS) within wrinkles mice. Specifically, we aim to understand how YXFMs enhance autophagy through the PI3K/AKT/FOXO path. METHODS: The active ingredients and medicinal uses of Ginseng, ligusticum wallichii, Ophiopogon, Schisandra, salvia, and astragalus were compiled using the BATMAN-TCM database. We also used Genecards, OMIM, and Disgenet files to identify the disease goals. A hierarchical diagram of "disease-drug-key targets" was generated using the Cytoscape programs. In addition, we established a target protein interaction (PPI) network using the STRING database. Then, the Cluster Profiler R package was used to conduct GO functional enrichment evaluation and KEGG pathway enrichment analyses of the targets. Based on the PPI system, we chose the top communicating targets and substances over molecular docking. In vivo studies were performed to validate these selections further. The mouse model was induced to study the damaged sinoatrial node (SAN) in mice with lower heart rates due to age-related changes. Electrocardiogram and Masson staining assessments were performed to obtain the results. The transmission electron microscope was used to assess the autophagy level of SAN cells. Western blot was employed to analyze the impact of YXFMs on protein expression in the PI3K/AKT/FOXO signaling process throughout SSS therapy in aging mice. RESULTS: One hundred forty-two active ingredients, 1858 targets, 1226 disease targets, and 266 intersection targets were obtained. The key targets of the PPI network encompassed TP53, AKT1, CTNNB1, INS, and TNF, among others. According to GO functional analysis, the mechanism underlying YXFMs in SSS treatment may primarily be associated with the control of ion transport across membranes, cardiac contraction, regulation of blood circulation, and other biological processes. Based on the results of KEGG pathway enrichment analysis, it was determined that they were mainly enriched in multiple pathways of signaling such as the PI3K-Akt signaling route, MAPK signaling process, AGE-RAGE signaling path, FOXO signaling path, HIF-1 signaling process, and several other paths. Molecular docking demonstrated that five compounds had excellent binding to the key candidate target proteins AKT1 and INS. Through the in vivo studies, we noticed notable effects when administering YXFMs. These effects included the suppression of aging-induced SSS, a decrease in the R-R interval, a rise in heart rate, a reduction in fibrosis, a boost in the autophagy process level, and a spike in the levels of expression of key protein molecules in the PI3K/AKT/FOXO signaling path. CONCLUSION: This research has made preliminary predictions about the potential of YXFMs in treating SSS. It suggests that YXFMs may have the ability to target key proteins and critical paths associated with the condition. Further testing has been conducted to discover new findings and evidence of ideas for tackling SSS triggered by aging.

The evaluation and optimization of the agricultural sustainable development based on a data-driven approach: A case from Northern Anhui.

The sustainable advancement of agriculture stands as the fundamental cornerstone of sustainable human progress. This study introduces a data-centric methodological framework founded upon the holistic delineation of measurement, feature assessment, and pathway enhancement for agricultural sustainability. Initially, the research articulates a comprehensive evaluative schema incorporating sub-dimensions encompassing agricultural production, agricultural economics, the agricultural resource environment, and rural society, grounded in sustainable development theory. Subsequently, it devises a methodological apparatus for assessing and enhancing sustainable development capabilities, employing entropy evaluation methods and exploratory spatial data analysis techniques. Employing North Anhui as a case study, the viability of this approach is substantiated. The empirical inquiry conducted within this article operationalizes comprehensive evaluation and explores pathways for optimizing agricultural sustainability, focusing on the period spanning 2011 to 2020 in Northern Anhui. The findings affirm the feasibility and efficacy of the data-driven approach. Recommendations derived from the empirical exploration of agricultural sustainability pathways at the local level offer valuable insights for governmental authorities and policymakers. This research endeavor could be extrapolated to other geographical locales worldwide, fostering innovative strides in the sustainable development of regional agriculture.

Diet specialization mediates drivers of Cucurbita herbivory in a semi-arid agroecosystem.

Herbivory is a major fitness pressure for plants and a key driver of crop losses in agroecosystems. Dense monocultures are expected to favor specialist herbivorous insects, particularly those who primarily consume crop species; yet, levels and types of herbivory are not uniform within regional cropping systems. It is essential to determine which local and regional ecological factors drive variation in herbivory in order to support functional agroecosystems that rely less on chemical inputs. Crops in the genus Cucurbita host a suite of both generalist and specialist herbivores that inflict significant damage, yet little is known about the relative contribution of these herbivores to variation in herbivory and how local- and landscape-scale Cucurbita resource concentrations, management practices, and natural enemies mediate this relationship. In this study, we tested whether three foundational ecological hypotheses influenced Cucurbita herbivory across 20 pumpkin fields in the semi-arid Southern High Plains Region of Texas. We used generalized linear mixed models and confirmatory path analysis to assess whether the Density-dependent Herbivory Hypothesis, Resource Concentration Hypothesis, or the Natural Enemies Hypothesis, could explain variation in Cucurbita herbivory and insect dynamics in the context of conventional agronomic practices. We found that herbivory increased over time, indicating that herbivores were causing sustained damage throughout the growing season. We also found that fields with higher local Cucurbita resources had lower herbivory, suggesting a resource dilution effect. Natural enemy communities were more abundant and taxonomically rich in sites with greater generalist herbivore abundance, though predator abundance declined over time, indicating that late-season crop fields are most at risk given high herbivory and low natural enemy-based control. Our findings also suggest that while local resource availability may drive the abundance and richness of arthropod communities, additional agronomic and phenological information is needed to anticipate herbivory risk in an agriculturally dominated landscape.

The relationship between attachment, primary emotions and positive/negative spirituality: a path analysis.

Objective: The present study investigates what may influence individuals to experience their religiosity/spirituality as either subjectively positive [religious or spiritual (r/s) wellbeing] or as negative (r/s struggles). Drawing on existing literature attachment insecurity and the seven primary emotions as outlined by Jaak Panksepp in Affective Neuroscience are identified as likely influences. Methods: The final sample consisted of 340 participants (age: M = 36, SD = 14.2; 68.5% = female), among which 65% self-identified as religious/spiritual. A path analysis was conducted to test a proposed mediation model in which the expected effects of primary emotions (B-ANPS) on r/s wellbeing (MI-RSWB) and r/s struggles (RSSS) were mediated through attachment insecurity (ECR-RD8). Results: The data indicated that attachment insecurity fully mediated the relationships between the primary emotions SADNESS and LUST with r/s struggles. Furthermore, the primary emotions FEAR and ANGER displayed small direct effects on both r/s struggles and r/s wellbeing. Overall, the model, which demonstrated excellent model fit, was able to explain 30% of the variance of r/s struggles, 24% of attachment insecurity and 5% of r/s wellbeing. Conclusions: The findings suggest that primary emotions such as SADNESS and LUST substantially explain r/s struggles and that these relationships seem to be mediated through attachment. Moreover, r/s struggles seem to be qualitatively distinct from r/s wellbeing. Finally, a moderate link between LUST and attachment suggests that sexuality plays a significant role in (adult) attachment processes.

Advances in ovarian tumor stem cells and therapy.

Ovarian cancer is considered the most lethal among all gynecological malignancies due to its early metastatic dissemination, extensive spread, and malignant ascites. The current standard of care for advanced ovarian cancer involves a combination of cytoreductive surgery and chemotherapy utilizing platinum-based and taxane-based agents. Although initial treatment yields clinical remission in 70-80% of patients, the majority eventually develop treatment resistance and tumor recurrence. A growing body of evidence indicates the existence of cancer stem cells within diverse solid tumors, including ovarian cancer, which function as a subpopulation to propel tumor growth and disease advancement by means of drug resistance, recurrence, and metastasis. The presence of ovarian cancer stem cells is widely considered to be a significant contributor to the unfavorable clinical outcomes observed in patients with ovarian cancer, as they play a crucial role in mediating chemotherapy resistance, recurrence, and metastasis. Ovarian cancer stem cells possess the capacity to reassemble within the entirety of the tumor following conventional treatment, thereby instigating the recurrence of ovarian cancer and inducing resistance to treatment. Consequently, the creation of therapeutic approaches aimed at eliminating ovarian cancer stem cells holds great potential for the management of ovarian cancer. These cells are regarded as one of the most auspicious targets and mechanisms for the treatment of ovarian cancer. There is a pressing need for a comprehensive comprehension of the fundamental mechanisms of ovarian cancer's recurrence, metastasis, and drug resistance, alongside the development of effective strategies to overcome chemoresistance, metastasis, and recurrence. The implementation of cancer stem cell therapies may potentially augment the tumor cells' sensitivity to existing chemotherapy protocols, thereby mitigating the risks of tumor metastasis and recurrence, and ultimately improving the survival rates of ovarian cancer patients.

The influence of travel time on perceived traveled distance varies by spatiotemporal scale.

The influence of travel time on perceived traveled distance has often been studied, but the results are inconsistent regarding the relationship between the two magnitudes. We argue that this is due to differences in the lengths of investigated travel distances and hypothesize that the influence of travel time differs for rather short compared to rather long traveled distances. We tested this hypothesis in a virtual environment presented on a desktop as well as through a head-mounted display. Our results show that, for longer distances, more travel time leads to longer perceived distance, while we do not find an influence of travel time on shorter distances. The presentation through an HMD vs. desktop only influenced distance judgments in the short distance condition. These results are in line with the idea that the influence of travel time varies by the length of the traveled distance, and provide insights on the question of how distance perception in path integration studies is affected by travel time, thereby resolving inconsistencies reported in previous studies.

In what ways does placeness affect people's behavior? Focusing on personal place attachment and public place image as connecting parameter.

Placeness is believed to play a significant role in enhancing the well-being and place-use of individuals, contributing profoundly to how spaces are experienced and interacted with. Despite its perceived importance, there is ongoing debate and insufficient clarity about how exactly placeness influences people's behavior. This study aims to bridge this gap by theorizing and investigating the pathways from placeness to people's behavioral intentions, emphasizing the roles of personal place attachment and public place image as pivotal mediators in this relationship. To explore these dynamics, we conducted a survey in Japan, examining the complex interplay between placeness and behavioral intentions, given their rich cultural heritage and modern urban pressures. We employed the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach for path analysis. The analysis suggests that placeness influences behavioral intention through personal place attachment. While placeness does affect public place image, this public image does not have an impact on behavioral intention. The results demonstrated that an individual's activities, experiences, and cognition of a place are significant factors in creating the intention to engage in word-of-mouth, recommendation, and revisiting behaviors. Policymakers, urban planners, and designers need to understand how to foster people's behavioral intentions when creating a place imbued with placeness.

Macrophage dynamics in prostate cancer: Molecular to therapeutic insights.

This review provides an in-depth examination of the role that tumor-associated macrophages (TAMs) play in the progression of prostate cancer (PCa), with a particular focus on the factors influencing the polarization of M1 and M2 macrophages and the implications of targeting these cells for cancer progression. The development and prognosis of PCa are significantly influenced by the behavior of macrophages within the tumor microenvironment. M1 macrophages typically exhibit anti-tumor properties by secreting pro-inflammatory cytokines such as interferon-gamma (IFN-γ) and tumor necrosis factor-alpha (TNF-α), thereby enhancing the immune response. Conversely, M2 macrophages contribute to tumor cell migration and invasion through the production of factors like arginase-1 (Arg1) and interleukin-10 (IL-10). This review not only explores the diverse factors that affect macrophage polarization but also delves into the potential therapeutic strategies targeting macrophage polarization, including the critical roles of non-coding RNA and exosomes in regulating this process. The polarization state of macrophages is highlighted as a key determinant in PCa progression, offering a novel perspective for clinical treatment. Future research should concentrate on gaining a deeper understanding of the molecular mechanisms underlying macrophage polarization and on developing effective targeted therapeutic strategies. The exploration of the potential of combination therapies to improve treatment efficacy is also emphasized. By emphasizing the importance of macrophages as a therapeutic target in PCa, this review aims to provide valuable insights and research directions for clinicians and researchers.

Null space-based control with gain modulation applied to a MARV in backward movement.

A controller is proposed to guide a multi-articulated robot vehicle (MARV) moving backwards, following a certain path. The ability to avoid fixed and moving obstacles is included, using the null space-based control technique to manage the conflicting tasks of following a path and avoiding obstacles. Additionally, control gains are modulated, thus reducing the risk of jackknifing. These new approaches are the contributions of the article. Results of laboratory-scale experiments with a MARV pushing one and two trailers are presented and discussed, which validate the proposed controller. Simulation results are also presented considering a MARV with three trailers, showing that the proposed controller can be adopted for larger articulated chains and another experiment that shows that it is possible to avoid moving obstacles.

Output-feedback path-following control of underactuated AUVs via singular perturbation and interconnected-system technique.

This paper focuses on the output-feedback control for path-following of underactuated autonomous underwater vehicles subject to multiple uncertainties and unmeasured velocities. First, a novel extended state observer is proposed to estimate the mismatched lumped disturbance and recover the unmeasured velocities. Based on this premise, to overcome the limitation of relying solely on the accurate kinematic model, a disturbance observer-based stabilizing controller is developed. The difference in bandwidths between the observer and the vehicle dynamics allows for a mathematical setup amenable to standard singular perturbation theory. In the fast mode, a kinematic observer is designed to reject system uncertainty caused by unknown attack angular velocity and prohibitive path-tangential angular velocity, using a novel physical perspective. In the slow mode, an interconnected-system control law is proposed by integrating the backstepping technique with the time scale decomposition method. Furthermore, the stability of the overall closed-loop system is established. Finally, simulation results are presented to demonstrate the effectiveness of the proposed method for path-following of underactuated autonomous underwater vehicles in the vertical plane.

A Robotic Solution for Precision Smoothing and Roughening of Precast Concrete Surfaces: Design and Experimental Validation.

Prefabricated construction has pioneered a new model in the construction industry, where prefabricated component modules are produced in factories and assembled on-site by construction workers, resulting in a highly efficient and convenient production process. Within the construction industry value chain, the smoothing and roughening of precast concrete components are critical processes. Currently, these tasks are predominantly performed manually, often failing to achieve the desired level of precision. This paper designs and develops a robotic system for smoothing and roughening precast concrete surfaces, along with a multi-degree-of-freedom integrated intelligent end-effector for smoothing and roughening. Point-to-point path planning methods are employed to achieve comprehensive path planning for both smoothing and roughening, enhancing the diversity of textural patterns using B-spline curves. In the presence of embedded obstacles, a biologically inspired neural network method is introduced for precise smoothing operation planning, and the A* algorithm is incorporated to enable the robot's escape from dead zones. Experimental validation further confirms the feasibility of the entire system and the accuracy of the machining path planning methods. The experimental results demonstrate that the proposed system meets the precision requirements for smoothing and offers diversity in roughening, affirming its practicality in the precast concrete process and expanding the automation level and application scenarios of robots in the field of prefabricated construction.

Analysis of Constraints on the Remote Application of Inverse Synthetic Aperture Laser Radar.

In order to achieve the remote application of inverse synthetic aperture laser radar for high resolution spatial situational awareness, it is essential to analyze the main factors that restrict its remote application. This study combines the range equation of inverse synthetic aperture lidar with the stimulated Brillouin threshold power equation to investigate the variation of laser transmitting power with distance. Additionally, by utilizing the excited Brillouin threshold power equation, laser linewidth formula, and pulse width characteristics of pulse signal, we examine the variation law of laser coherence that meets corresponding power requirements at different distances. The results indicate that a detection distance of 22 km and below can be achieved using continuous fiber lasers without compensation. Coherence compensation is necessary for distances between 22 km and 57 km. For distances ranging from 57 km to 3000 km, pulsed solid-state lasers are used to analyze coherence and conclude that imaging non-cooperative targets within this range is feasible. It is observed that coherence compensation is required from 57 km to 2179 km, becoming more challenging after 2000 km. Furthermore, pulsed solid-state lasers can still be utilized for imaging cooperative targets within a range of 2179-3273 km; however, coherence compensation remains necessary and becomes increasingly difficult. Finally, several coherent length compensation schemes are proposed in order to extend the imaging range of inverse synthetic aperture LiDAR to approximately 3000 km.

Coverage Planning for UVC Irradiation: Robot Surface Disinfection Based on Swarm Intelligence Algorithm.

Ultraviolet (UV) radiation has been widely utilized as a disinfection strategy to effectively eliminate various pathogens. The disinfection task achieves complete coverage of object surfaces by planning the motion trajectory of autonomous mobile robots and the UVC irradiation strategy. This introduces an additional layer of complexity to path planning, as every point on the surface of the object must receive a certain dose of irradiation. Nevertheless, the considerable dosage required for virus inactivation often leads to substantial energy consumption and dose redundancy in disinfection tasks, presenting challenges for the implementation of robots in large-scale environments. Optimizing energy consumption of light sources has become a primary concern in disinfection planning, particularly in large-scale settings. Addressing the inefficiencies associated with dosage redundancy, this study proposes a dose coverage planning framework, utilizing MOPSO to solve the multi-objective optimization model for planning UVC dose coverage. Diverging from conventional path planning methodologies, our approach prioritizes the intrinsic characteristics of dose accumulation, integrating a UVC light efficiency factor to mitigate dose redundancy with the aim of reducing energy expenditure and enhancing the efficiency of robotic disinfection. Empirical trials conducted with autonomous disinfecting robots in real-world settings have corroborated the efficacy of this model in deactivating viruses.

Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot.

Path planning creates the shortest path from the source to the destination based on sensory information obtained from the environment. Within path planning, obstacle avoidance is a crucial task in robotics, as the autonomous operation of robots needs to reach their destination without collisions. Obstacle avoidance algorithms play a key role in robotics and autonomous vehicles. These algorithms enable robots to navigate their environment efficiently, minimizing the risk of collisions and safely avoiding obstacles. This article provides an overview of key obstacle avoidance algorithms, including classic techniques such as the Bug algorithm and Dijkstra's algorithm, and newer developments like genetic algorithms and approaches based on neural networks. It analyzes in detail the advantages, limitations, and application areas of these algorithms and highlights current research directions in obstacle avoidance robotics. This article aims to provide comprehensive insight into the current state and prospects of obstacle avoidance algorithms in robotics applications. It also mentions the use of predictive methods and deep learning strategies.

Localized Path Planning for Mobile Robots Based on a Subarea-Artificial Potential Field Model.

The artificial potential field method has efficient obstacle avoidance ability, but this traditional method suffers from local minima, unreasonable paths, and sudden changes in heading angles during obstacle avoidance, leading to rough paths and increased energy consumption. To enable autonomous mobile robots (AMR) to escape from local minimum traps and move along reasonable, smooth paths while reducing travel time and energy consumption, in this paper, an artificial potential field method based on subareas is proposed. First, the optimal virtual subgoal was obtained around the obstacles based on the relationship between the AMR, obstacles, and goal points in the local environment. This was done according to the virtual subgoal benefit function to solve the local minima problem and select a reasonable path. Secondly, when AMR encountered an obstacle, the subarea-potential field model was utilized to solve problems such as path zigzagging and increased energy consumption due to excessive changes in the turning angle; this helped to smooth its planning path. Through simulations and actual testing, the algorithm in this paper demonstrated smoother heading angle changes, reduced energy consumption, and a 10.95% average reduction in movement time when facing a complex environment. This proves the feasibility of the algorithm.