Movement Strategies Research Articles

Evaluation of a time-varying cut-off frequency low-pass filter for assessing knee joint moments and ACL injury risk

ABSTRACT Conventional low-pass filtering of 3D motion capture signals prior to estimating knee joint moments and ACL injury risk has known limitations. This study aimed to evaluate the fractional Fourier filter (FrFF), which employs a time-varying cut-off frequency, for assessing peak knee moments during common ACL injury risk screening tasks. Ground reaction force and motion data were collected from 23 team sport athletes performing 45° unanticipated sidesteps and drop jumps. Peak knee abduction, internal rotation and non-sagittal moments were estimated using inverse dynamics after five different low-pass filter approaches were applied (FrFF vs. four variations of a fourth-order Butterworth filter). The FrFF produced peak knee moments larger than “matched” (i.e. force and motion cut-off frequencies were equivalent) and closer to “unmatched” (i.e. force and motion cut-offs were different) Butterworth filter approaches and removed problems with representing foot-to-ground impact peaks. Participants with larger peak moments were identified as “at risk” of injury irrespective of filter approach, but the FrFF identified “at risk” classifications conventional approaches did not. Preliminary evidence suggests that the FrFF displays enhanced sensitivity to movement strategies that induce high knee loads. This was most evident for sidestepping, with more research warranted to optimise the FrFF for drop jumps.

Research on motion control strategy of athlete muscle training based on blockchain and visual image analysis

Muscle training is an important part of athletes’ physical training. Its goal is to keep athletes in high intensity and improve sports performance in physical training. With the continuous improvement of the level of competitive sports, there are still many problems in the training of competitive athletes. The research on the control strategies of some technical movements in the process of athletes’ muscle development would help to improve the efficiency and effect of athletes’ training. By analyzing and quant description of muscle movement control process based on blockchain and visual image processing technology, the muscle movement control rule is discussed and then a complete movement database is constructed. At the same time, combined with the sports experiment method and cognitive behavioral theory, this paper analyzed the exercise load, exercise time allocation, muscle training time allocation methods and the corresponding muscle training strategy selection methods under different muscle states, providing theoretical basis for athletes to conduct muscle strength training scientifically and efficiently. This paper first analyzed the importance of athletes’ muscle training action control. After that, the research was mainly carried out from the following two aspects. The first is to analyze the motion control strategy of athlete muscle training based on blockchain and visual image, and summarize its characteristics. The second is to use electronic imaging technology to analyze the data related to posture control in athletes’ muscle training, and explore the characteristics and changes of muscle posture. At last, this paper put forward relevant algorithms about visual images and conducted experimental research on athletes’ physical indicators and performance under different muscle training according to the research in this paper. It was concluded that the score ratio of athletes’ performance after muscle training action control was 7.39% higher than that of general muscle training. Therefore, it is very important to strengthen the research of movement technology in muscle training and analyze the influence of some training control strategies on the development of athletes’ muscles in training.

Eye Movement Patterns in Russian-Speaking Adolescents with Differing Reading Comprehension Proficiency: Exploratory Scanpath Analysis

Previous research has indicated that individuals with varying levels of reading comprehension (often used as a proxy for general cognitive ability) employ distinct reading eye movement patterns. This exploratory eye-tracking study aimed to investigate the text-reading process in adolescents with differing reading comprehension, specifically examining how these differences manifest at the global eye movement level through scanpath analysis. Our findings revealed two distinct groups of scanpaths characterized by statistically significant differences in eye movement parameters. These groups were identified as “fast readers” and “slow readers”. Both groups exhibited similar oculomotor performance during the initial reading. However, significant differences emerged when they reread and revisited the text. Notably, these findings align with prior research conducted with different samples and languages, although discrepancies emerged in saccade amplitude and first-pass reading behavior. This study contributes to the understanding of how reading comprehension levels are reflected in global eye movement strategies among adolescents. However, limitations inherent in the experimental design, particularly the potential influence of the task on reading patterns, warrant further investigation. Future research should aim to explore these phenomena in more naturalistic reading settings, employing a design specifically tailored to capture the nuances of spontaneous reading behavior.

Research on Bionic Robot Motion Control Based on Reinforcement Learning

This research explores the application of reinforcement learning (RL) to enhance the motion control of bio-inspired robots across various environments. Focusing on underwater, terrestrial, and aerial robotic models, the study integrates model-free Q-learning, Deep Q Network (DQN), State-Action-Reward-State-Action (SARSA), and Double Deep Q Network (DDQN) algorithms. These methods are employed to achieve adaptive and efficient movement strategies without relying on pre-defined environmental models. The methodologies range from real-time data capture using live camera feeds for terrestrial robots to simulating aquatic and flight dynamics in controlled environments. Experimental results confirm the efficacy of these RL methods, demonstrating significant improvements in the robots' ability to adapt to dynamic and unknown environments, optimize movement efficiency, and navigate complex scenarios. The findings suggest a promising direction for future robotic applications, emphasizing the need for further research on optimizing these algorithms and expanding their real-world applicability. This study highlights the potential of RL to revolutionize robotic motion control, making robots more versatile and capable in varied and unpredictable settings.

Political Communication Research is Unprepared for the Far Right

ABSTRACT In this introductory piece to a special issue of the Forum, we explore the inadequacies of the field of political communication in addressing the rising threats posed by illiberalism and the far right. We argue that the discipline’s frameworks, developed within the context of Western liberal democracies, are ill-equipped to tackle the complexities and self-reflexive strategies of contemporary far-right movements and actor types. These formations exploit liberal norms and practices to ultimately undermine and dismantle democratic values. We call for more “democratic clarity,” urging political communication scholars to adopt a clear stance in defense of democratic principles and to develop more robust conceptual tools to accurately classify and understand far-right actors. We introduce the other discussion pieces featured in this special section and ultimately point to actionable items meant to move the field forward.

Foot Kinematics of Elite Female 59 kg Weightlifters in the 2018–2021 World Championships

Background/Objectives: Research on elite weightlifting performance is crucial for understanding the underlying attributes of efficient techniques. This study aimed to analyze the foot characteristics of elite female weightlifters in the 59 kg category during the snatch. Methods: Publicly available videos from the International Weightlifting Federation World Weightlifting Championships (2018–2021) were analyzed. Excluding the 2020 competition due to the COVID-19 pandemic and more unsuccessful attempts, a total of 20 videos were selected for kinematic analysis using Kenova video analysis software. Variables included the horizontal foot distance in the start and catch phases, horizontal displacement of sideway leg separation, and maximum vertical heel height of each foot. Results: The results revealed small to moderate significant negative correlations between snatch performance and maximum heel height (right: r = −0.28, p < 0.05; left: r = −0.332 p < 0.01). Snatch performance also demonstrated a small to moderate negative correlation with sideway leg separation and foot distance in the catch phase (r = −0.275, p < 0.01; r = −0.467, p < 0.01, respectively). Maximum heel height exhibited a very strong positive correlation between feet (r = 0.853, p < 0.01). Conclusions: A relatively narrower stance was found to be more beneficial for elite weightlifter performance. Strong coordination suggests advanced movement strategies in this complex lift. These findings contribute to the existing knowledge on weightlifting techniques and offer valuable insights for athletes and coaches seeking to improve performance in competitive environments.

Reinforcement Learning with Multi-Policy Movement Strategy for Weakly Supervised Temporal Sentence Grounding

Temporal grounding involves identifying the target moment based on the provided sentence in an untrimmed video. In weakly supervised temporal grounding studies, existing temporal sentence grounding methods face challenges in (1) learning semantic alignment between the candidate window and language query and (2) identifying accurate temporal boundaries during the grounding process. In this work, we propose a reinforcement learning (RL)-based multi-policy movement framework (MMF) for weakly supervised temporal sentence grounding. We imitate the behavior of human beings when grounding specified content in a video, starting from a coarse location and then identifying fine-grained temporal boundaries. The RL-based framework initially sets a series of candidate windows and learns to adjust them step-by-step by maximizing the rewards, indicating the semantic alignment between the current window and the query. To better learn the alignment, we propose a Gaussian-based Dual-Alignment Module (GDAM) which combines the strengths of both scoring-based and reconstruction-based alignment methods, addressing the issues of negative sample bias and language bias. We also employ the multi-policy movement strategy (MMS) which grounds the temporal position in a coarse-to-fine manner. Extensive experiments demonstrate that our proposed method outperforms existing weakly supervised algorithms, achieving state-of-the-art performance on the Charades-STA and ActivityNet Captions datasets.

State-of-the-Art Flocking Strategies for the Collective Motion of Multi-Robots

The technological revolution has transformed the area of labor with reference to automation and robotization in various domains. The employment of robots automates these disciplines, rendering beneficial impacts as robots are cost-effective, reliable, accurate, productive, flexible, and safe. Usually, single robots are deployed to accomplish specific tasks. The purpose of this study is to focus on the next step in robot research, collaborative multi-robot systems, through flocking control in particular, improving their self-adaptive and self-learning abilities. This review is conducted to gain extensive knowledge related to swarming, or cluster flocking. The evolution of flocking laws from inception is delineated, swarming/cluster flocking is conceptualized, and the flocking phenomenon in multi-robots is evaluated. The taxonomy of flocking control based on different schemes, structures, and strategies is presented. Flocking control based on traditional and trending approaches, as well as hybrid control paradigms, is observed to elevate the robustness and performance of multi-robot systems for collective motion. Opportunities for deploying robots with flocking control in various domains are also discussed. Some challenges are also explored, requiring future considerations. Finally, the flocking problem is defined and an abstraction of flocking control-based multiple UAVs is presented by leveraging the potentials of various methods. The significance of this review is to inspire academics and practitioners to adopt multi-robot systems with flocking control for swiftly performing tasks and saving energy.

Partial migration pays off in black-faced cormorants: insights from post-breeding GPS tracking

Seasonal variation in food availability or adverse weather patterns can create challenging conditions for year-round survival. Birds experiencing such fluctuations may migrate to locations with better food availability in the non-breeding period. While some species are obligate migrants, others are facultative migrants where various post-breeding strategies exist within populations. Several cormorant and shag species are facultative migrants with a range of post-breeding movement strategies within populations. Currently, most of the information available on cormorant post-breeding strategies originates from banding studies and little is known about their movements, time budget or habitat use during the non-breeding period. In the present study, Australian endemic black-faced cormorants (Phalacrocorax fuscescens), breeding on Notch Island, Victoria, were tracked with GPS data loggers during the non-breeding period. Different post-breeding strategies were observed. Individuals were either resident (N = 36, 69%), remaining within a short distance of the colony (16.7 ± 2.2 km) or migratory (N = 16, 31%), travelling greater distances (250.7 ± 24.4 km) to establish a new central place foraging location. Data from individuals which covered the entire non-breeding period indicated that, across strategies, individual birds had one area of residency during the non-breeding period. Migratory individuals were found to have lower daily activity levels, spending less time flying and foraging, than resident individuals during the early non-breeding period, possibly indicating that they had access to greater prey resources. Regardless of the post-breeding strategy, individuals utilised foraging locations that were of similar seabed depths year-round suggesting individual specialisation in prey resources or foraging habitats.

The Experiences of Motor Skill Development in Children with Autism Spectrum Disorder (ASD) Reflected through Parental Responses.

Background/Objectives: Understanding movement development in children with autism spectrum disorder (ASD) is critical for creating effective intervention strategies. This study aims to explore parental perspectives on the movement development of children with ASD, focusing on identifying common challenges and successful strategies. The objective is to analyze the experiences of parents to highlight the most effective approaches to support motor, communication, and social skills development in these children. Methods: Using a qualitative approach, we conducted in-depth interviews with parents of children with ASD. The data were analyzed using open and selective coding to identify key themes related to movement development challenges and strategies. The analysis included cross-referencing with the existing literature to support parental insights. Results: This study identified several key themes, including communication barriers, social interaction difficulties, and the importance of personalized movement programs. Parents reported significant challenges in understanding and addressing their children's movement needs, particularly in group settings. However, activities such as water programs, music and dance, and animal-assisted therapies were found to be highly engaging. Motivation was a critical factor, with rewards and active parental involvement enhancing participation. Conclusions: This study highlights the crucial role of a supportive environment, including professional guidance and family support, in the success of movement development programs.

Migratory strategies across an ecological barrier: is the answer blowing in the wind?

BackgroundEcological barriers can shape the movement strategies of migratory animals that navigate around or across them, creating migratory divides. Wind plays a large role in facilitating aerial migrations and can temporally or spatially change the challenge posed by an ecological barrier, with beneficial winds potentially converting a barrier into a corridor. Here, we explore the role wind plays in shaping initial southbound migration strategy among individuals breeding at two sites along an ecological barrier.MethodsUsing GPS satellite transmitters, we tracked the southbound migrations of Short-billed Dowitchers (Limnodromus griseus caurinus) from two breeding sites in Alaska to nonbreeding sites in coastal Mexico. The breeding sites were positioned in distinct regions along an ecological barrier – the Gulf of Alaska. We investigated potential differences in migratory timing, wind availability, and tailwind support en route across the Gulf of Alaska between individuals breeding at the two sites.ResultsRoute choice and arrival timing to wintering sites differed markedly between the two breeding sites: individuals departing from the more westerly site left at the same time as those from further east but crossed the Gulf of Alaska farther west and arrived along the Pacific coast of Mexico an average of 19 days earlier than their counterparts. Dowitchers from both sites departed with slight tailwinds, but once aloft over the Gulf of Alaska, birds from the more westerly site had up to twelve times more tailwind assistance than birds from the more easterly one.ConclusionsThe distinct migration strategies and degree of wind assistance experienced by birds at these two breeding sites demonstrates how differences in wind availability along migratory routes can form the basis for intraspecific variation in migration strategies with potential carryover effects. Future changes in wind regimes may therefore interact with changes in habitat availability to influence migration patterns and migratory bird conservation.

Coexistence states for a Lotka–Volterra competitive model with aggressive movement strategy

This paper is concerned with a model of reaction–diffusion–advection equations arising in ecology. The equations model a situation in which the foreign species and the native species are both assumed to be competing for space in the same ecological niche, and the foreign species is just random diffusion while the native species is “braver” — a combination of random diffusion and a directed movement up the gradient of the foreign species. Our aim is to give the necessary and sufficient conditions for the coexistence of the foreign species and native species. For this, we first establish an a priori estimate result. Then we apply eigenvalue theory and homogenization principle to derive the necessary conditions for the coexistence. Finally, the sufficient conditions for the coexistence are given by using a global bifurcation method.

PartwiseMPC: Interactive Control of Contact‐Guided Motions

AbstractPhysics‐based character motions remain difficult to create and control. We make two contributions towards simpler specification and faster generation of physics‐based control. First, we introduce a novel partwise model predictive control (MPC) method that exploits independent planning for body parts when this proves beneficial, while defaulting to whole‐body motion planning when that proves to be more effective. Second, we introduce a new approach to motion specification, based on specifying an ordered set of contact keyframes. These each specify a small number of pairwise contacts between the body and the environment, and serve as loose specifications of motion strategies. Unlike regular keyframes or traditional trajectory optimization constraints, they are heavily under‐constrained and have flexible timing. We demonstrate a range of challenging contact‐rich motions that can be generated online at interactive rates using this framework. We further show the generalization capabilities of the method.

Predicting the Presence of Pain in Youth Baseball Pitchers Using the Concept of Biomechanical Efficiency.

Increases in peak shoulder distraction force and peak elbow valgus torque may influence throwing-arm pain and injury risk in youth pitchers. The purpose of this study was to determine whether shoulder distraction force and elbow valgus torque while accounting for anthropometrics and pitch velocity can predict the presence of pain in youth baseball pitchers. It was hypothesized that throwing-arm pain could be predicted using the concept of biomechanical efficiency, where a pitcher who is less efficient (having higher force or torque with the same pitch velocity) is more likely to experience pain. Descriptive laboratory study. A total of 38 youth baseball pitchers (mean age, 13.3 ± 1.7 years) were divided into a pain group and pain-free group based on presence of throwing-arm pain as reported on a health history questionnaire. Each pitcher threw 3 maximal-effort fastballs to a catcher at regulation distance, and kinematics were measured using an electromagnetic motion-capture system (minimum 100 Hz). Height and weight as well as mean peak shoulder distraction force, peak elbow valgus torque, and pitch velocity across the 3 trials were evaluated. Logistic regression analyses determined whether shoulder distraction force or elbow valgus torque could predict the presence of throwing-arm pain when holding anthropometrics (body weight for shoulder distraction force; body weight and height for elbow valgus torque) and pitch velocity constant. Shoulder distraction force significantly predicted the presence of throwing-arm pain after accounting for body weight and pitch velocity (χ2 = 9.49; P = .023). Specifically, for every 1-N increase in peak shoulder distraction force while holding body weight and pitch velocity constant, there was a 0.6% increased likelihood of experiencing throwing-arm pain. Elbow valgus torque could not predict the presence of pain when holding body weight, height, and pitch velocity constant. The models demonstrated that increases in peak shoulder distraction forces when holding pitch velocity and body weight constant increased a youth baseball pitcher's likelihood of experiencing throwing-arm pain. The study results support the concept of the biomechanical efficiency framework by offering evidence that maintaining pitch velocity with a lower joint load led to a lower likelihood of pain. Results suggest that practicing efficient movement strategies can decrease the likelihood of experiencing throwing-arm pain while maintaining performance.

Weighted average algorithm: a novel meta-heuristic optimization algorithm based on the weighted average position concept

To address the ever-increasing complexity of real-world engineering challenges, meta-heuristic algorithms have been extensively studied and applied. However, balancing exploration and exploitation remains a significant challenge. In this paper, a novel meta-heuristic optimization algorithm based on the weighted average position concept, and named weighted average algorithm (WAA), is proposed and implemented. In this algorithm, the weighted average position for the whole population is first established at each iteration. Subsequently, WAA applies one of two movement strategies to balance exploration and exploitation, determined by a parameter function that depends on random constants and iteration numbers. To validate the effectiveness and reliability of WAA, it is applied to various optimization challenges, amongst which unconstrained benchmark functions and constrained engineering challenges. Based on the Friedman and Wilcoxon analyses, it can be concluded that the proposed algorithm obtained the best performance for the considered benchmark functions and engineering problems. The WAA is applied to prediction and optimization of surface waviness in Wire Arc Additive Manufacturing (WAAM) components. First, two prediction models relating WAAM process parameters and surface waviness are established based on an Artificial Neural Network (ANN) optimized by WAA, and Particle Swarm Optimization (PSO), respectively. The WAA optimized ANN (WAA/ANN) model outperforms both the standard ANN models and those optimized by PSO. Finally, leveraging the developed WAA/ANN prediction model, WAA and other optimization algorithms are applied to minimize waviness of a WAAM component, with WAA exhibiting promising performance.

Research on Cooperative Tracking of Multiple Agents on Heterogeneous Ground

Abstract Pursuit-evasion scenarios are typical and significant area of study multi-agent behaviours. While previous research has primarily focused on training pursuit strategies on idealized flat, this paper explores pursuit strategies on heterogeneous ground that rely on ground features from the effects of friction and viscous forces. Since agent interacts with heterogeneous ground and changes its acceleration, we perform multi-agent modelling. Aiming at the multi-agent deep deterministic policy gradient (MADDPG) algorithm’s low training efficiency and slow convergence speed in pursuit learning, we use the prioritized experience selection mechanism of MADDPG algorithm (PES-MADDPG) which improve the experience extraction mechanism based on the policy evaluation function error and the experience extraction training frequency. With this approach, the design of rewards results in faster convergence of reward values. The experimental findings confirm that the suggested method delivers better performance and effectiveness for pursuers and evaders on heterogeneous ground, and both can acquire the relevant movement strategies through training.

Influence of medial longitudinal arch flexibility on lower limb joint coupling coordination and gait impulse

BackgroundA causal link exists between structural differences in the foot and alterations in the lower limb biomechanics, which might predispose an individual to develop characteristic musculoskeletal disorders. Research questionThis study aimed to determine how the foot structural characteristics, as represented by the medial longitudinal arch flexibility, affect lower limb joint coupling coordination and anterior-posterior ground reaction impulses (GRIs) during walking and running. MethodsFollowing the calculation of arch height flexibility, a total of fifty-four physically active males were grouped and completed gait experiments to collect kinematic and kinetic data synchronously. Inter-joint coordination and variability were calculated from the angle-angle plots of knee-hip, ankle-knee, and metatarsophalangeal (MTP)-ankle couplings based on an optimized vector coding technique. ResultsOur results indicate that coupling coordination of interest and its variability, as well as anterior-posterior GRIs, could potentially be influenced due to differences in arch height flexibility. Notably, the individuals with stiff arches exhibited significantly greater coordination variabilities during the early stance for both ankle-knee and MTP-ankle coordination yet significantly smaller for MTP-ankle coordination variabilities during the mid-stance phase. Furthermore, combining the statistical parametric mapping analysis results, the flexible arches experienced a greater proportion of GRIs in the anterior-posterior direction. SignificanceIn conclusion, these observations demonstrated that variations in arch flexibility led to differences in lower limb joint coordination variabilities and GRIs during gait. This fresh insight into inter-joint coordinative function may be useful for enhancing foot motion strategies based on arch structural characteristics.

Overlapping Structure Detection in Protein-Protein Interaction Networks Using a Modified Version of Particle Swarm Optimization

In today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and hard optimization problem. One of the main difficulties in identifying overlapping protein complexes is the accuracy of the partitioning results. In order to accurately identify the overlapping structure of protein complexes, this paper has proposed an overlapping complex detection algorithm termed OCDPSO-Net, which is based on PSO-Net (a well-known modified version of the particle swarm optimization algorithm). The framework of the OCDPSO-Net method consists of three main steps, including an initialization strategy, a movement strategy for each particle, and enhancing search ability in order to expand the solution space. The proposed algorithm has employed the partition density concept for measuring the partitioning quality in PPI network complexes and tried to optimize the value of this quantity by applying the line graph concept of the original graph representing the protein interaction network. The OCDPSO-Net algorithm is applied to a Collins PPI network and the obtained results are compared with different state-of-the-art algorithms in terms of precision ( ), recall ( ), and F-measure ( ). Experimental results confirm that the proposed algorithm has good clustering performance and has outperformed most of the existing recent overlapping algorithms. .

KoPer: School Lıteracy Movement Strategy To Strengthen Readıng And Wrıtıng Skılls

The School Literacy Movement is an activity program that focuses on reading and writing skills. The School Literacy Movement was formed due to the low interest in reading and writing of students. So that the purpose of this school literacy movement is to achieve maximum quality of education quality related to reading and writing skills. The School Literacy Movement is a very important thing to develop through a strategy, namely KoPer (Literacy Group). KoPer (Literacy Group) has the purpose of strengthening reading and writing skills. This study aims to strengthen students' reading and writing skills through the school literacy movement strategy at Gonilan 02 State Elementary School, namely with KoPer (Literacy Group). The methods used in this research are observation, interview and documentation methods with the subjects of students, class teachers and the principal of Gonilan 02 State Elementary School. The results of this study are that there are three stages in the school literacy movement; the habituation stage, the learning stage and the development stage. Of the three stages, Gonilan 02 State Elementary School has implemented well through 15-minute reading activities, guided reading, shared reading, organizing a literacy-rich environment, compiling and making schedules, library visits, wall magazines and reading corners in class. In this KoPer (Literacy Group) there are strategies implemented by the school, namely, Digit Literacy, Library, Around the Region, and Literacy-Based Environments. This shows that KoPer(Literacy Group) is an alternative way to strengthen reading and writing skills for primary school students reading and writing skills for primary school students.

On the move: Influence of animal movements on count error during drone surveys.

The use of remote sensing to monitor animal populations has greatly expanded during the last decade. Drones (i.e., Unoccupied Aircraft Systems or UAS) provide a cost- and time-efficient remote sensing option to survey animals in various landscapes and sampling conditions. However, drone-based surveys may also introduce counting errors, especially when monitoring mobile animals. Using an agent-based model simulation approach, we evaluated the error associated with counting a single animal across various drone flight patterns under three animal movement strategies (random, directional persistence, and biased toward a resource) among five animal speeds (2, 4, 6, 8, 10 m/s). Flight patterns represented increasing spatial independence (ranging from lawnmower pattern with image overlap to systematic point counts). Simulation results indicated that flight pattern was the most important variable influencing count accuracy, followed by the type of animal movement pattern, and then animal speed. A awnmower pattern with 0% overlap produced the most accurate count of a solitary, moving animal on a landscape (average count of 1.1 ± 0.6) regardless of the animal's movement pattern and speed. Image overlap flight patterns were more likely to result in multiple counts even when accounting for mosaicking. Based on our simulations, we recommend using a lawnmower pattern with 0% image overlap to minimize error and augment drone efficacy for animal surveys. Our work highlights the importance of understanding interactions between animal movements and drone survey design on count accuracy to inform the development of broad applications among diverse species and ecosystems.