Larger Step Length Research Articles

체조 뜀틀 다리 벌려 넘기 동작의 성공적인 수행을 위한 운동학적 비교분석

Objectives This study was conducted for the purpose of improving gymnastic function by dividing the movement into 4 phases and 3 sections targeting 2 groups of 5 people for the purpose of successful performance during the gymnastic jumping frame jump movement. Methods In the experiments of this study, time factors, hand positions, stride length, and angle variables were compared by group through a motion analysis program. Results Frst, the time required to perform the movement was long in the successful group due to the upward movement of the center of the body and the upward change in flight time required to stably cross the jumping frame. Second, the vertical height of the center of the body was higher in the successful group in the phase of placing hands on the jumping frame (E3), resulting in an increase in flight time. showed low results. Third, in order to raise the upper body and successfully cross the vault, the head, elbow, and body angles were greatly extended in the successful group. In order to increase the ground reaction force and improve the vertical speed in the suc-cessful group, the knee angle showed a larger flexion result. Fourth, the successful group showed a relatively large step length corresponding to the horizontal distance in the direction of movement. This is considered to be a factor necessary for performing a motion in which no part of the body touches the jumping frame. Conclusions For a successful vaulting jump, you must stare straight ahead, stamp your feet, and reach your hands farther away to touch the front of the back of the hoop. While pushing your hands on the jumping frame, raise your upper body, and at this time, make your hips and upper body connected to the body horizontal. You have to jump over the hoop with your knees extended and your legs spread, and you must perform a successful motion that reduces the amount of impact by slightly bending your knees as you land.

Bird movement patterns in an agricultural landscape are mediated by both habitat conditions and traits

AbstractAlterations of the landscape following agricultural expansion and intensification affect animal movement patterns in the resulting mosaic of fragments and surrounding matrix. Here, we analyze the observed movement patterns of 34 individuals from nine tropical bird species from a rapidly changing agricultural landscape in Kenya. We deconstructed the movement patterns into their three components: step length, turn angles, and displacement and categorized them into two states: area restrictive and expansive movement. Using hidden Markov models, mixed models, and species traits, we showed that movement of birds in the fragments comprised of short step lengths and small displacements, characteristic of area restrictive movement to exploit high‐quality habitats. On the contrary, movement in the matrix comprised of long step lengths and large displacements, characteristic of area expansive movement to explore or pass‐through poorer habitats. The responses of movement components to fragments and the surrounding matrix were mediated by species traits. Habitat specialists showed stronger boundary response, shorter step lengths, and smaller displacements than habitat generalists in both the fragments and the matrix. Their strong preferences for the fragments, coupled with low flight capabilities can make movement in the matrix particularly difficult. Whereas, at the landscape scale, habitat generalist omnivores and habitat specialist frugivores had larger step lengths than the other guilds, as they use the matrix for resources or as a conduit to movement. Therefore, the habitat fragments are intensely utilized and of conservation importance. The matrix quality and permeability can promote animal space use and movement.

Improving the transferability of adversarial examples via direction tuning

In the transfer-based adversarial attacks, adversarial examples are only generated by the surrogate models and achieve effective perturbation in the victim models. Although considerable efforts have been developed on improving the transferability of adversarial examples generated by transfer-based adversarial attacks, our investigation found that, the big convergence speed deviation along the actual and steepest update directions of the current transfer-based adversarial attacks is caused by the large update step length, resulting in the generated adversarial examples can not converge well. However, directly reducing the update step length will lead to serious update oscillation so that the generated adversarial examples also can not achieve great transferability to the victim models. To address these issues, a novel transfer-based attack, namely direction tuning attack, is proposed to not only decrease the angle between the actual and steepest update directions in the large step length, but also mitigate the update oscillation in the small sampling step length, thereby making the generated adversarial examples converge well to achieve great transferability on victim models. Specifically, in our direction tuning attack, we first update the adversarial examples using the large step length, which is aligned with the previous transfer-based attacks. In addition, in each large step length of the update, multiple examples sampled by using a small step length. The average gradient of these sampled examples is then used to reduce the angle between the actual and steepest update directions, as well as mitigates the update oscillation by eliminating the oscillating component. By doing so, our direction tuning attack can achieve better convergence and enhance the transferability of the generated adversarial examples. In addition, a network pruning method is proposed to smooth the decision boundary, thereby further decreasing the update oscillation and enhancing the transferability of the generated adversarial examples. The experiment results on ImageNet demonstrate that the average attack success rate (ASR) of the adversarial examples generated by our method can be improved from 87.9% to 94.5% on five victim models without defenses, and from 69.1% to 76.2% on eight advanced defense methods, in comparison with that of latest gradient-based attacks. Code is available at https://github.com/HaloMoto/DirectionTuningAttack.

Error analyses and evaluation for solving burnup equations with MMPA method

The Mini-Max Polynomial Approximation (MMPA) is a new method to solve burnup equations, which has attracted much attention due to its advantages of good computational accuracy and efficiency. Understanding its error mechanism is significant for its application in practical burnup calculations. In this research, a mathematical model is proposed to clarify the error mechanism of the MMPA method for the burnup calculation. Then the coefficients of the MMPA method with different orders are given by the Remez algorithm. The errors of the MMPA method with different orders in burnup calculation are compared and analyzed, especially in single-step burnup calculation and infinite-step burnup calculation. Three cases are selected to verify the correctness of the mathematical error model, including fresh fuel burnup, depleted fuel burnup and decay calculation. The results show that when the order is greater than 36, the calculation accuracy of the MMPA method is less than the numerical noise of double precision calculation. As the order increases, the step length sensitivity of the MMPA method decreases. Finally, the computational accuracy and computational efficiency of the MMPA method with different orders are compared with those of the 16th order Chebyshev Rational Approximation Method (CRAM). The accuracy of the 16th order CRAM is between the 32nd and 36th order MMPA method. And the computation time of MMPA methods below order 76 is less than that of the 16th order CRAM. The theoretical analysis results of the mathematical error model are consistent with the numerical results. Then several best practices for solving burnup equations using the MMPA method are presented: (1) It is recommended to use the MMPA method with orders above 36 and below 76, whose accuracy and efficiency are better than 16th order CRAM in different degrees. (2) In multi-physics coupled computation which may require a strategy of large step length calculation, increasing the order of the MMPA method can not only improve the computational accuracy but also improve the computational efficiency.

Sex Differences in Spatiotemporal Gait Parameters of Transtibial Amputees.

Research addressing lower limb amputee gait and prosthetic design often focuses on men, despite female lower limb amputees having different risk factors and lower success with their prosthetics overall. It is widely agreed that sex differences exist in able-bodied gait, but research analyzing sex differences in amputee gait is rare. This study compared male and female transtibial amputee gait to ascertain potential sex differences. Forty-five transtibial amputees were asked to walk at their self-selected speed, and spatiotemporal gait data were obtained. Both the mean and variability metric of parameters were analyzed for 10 male and 10 female participants. For all participants, amputated limbs had a shorter stance time, longer swing time, and larger step length. Females had a 10% shorter stance time and 26% larger normalized step and stride length than males. Female participants also walked over 20% faster than male participants. Finally, significant interactions were found in the mean and variability metric of stride velocity, indicating greater variability in women. These findings suggest that sex differences exist in transtibial amputee gait, offering possible explanations for the different comorbidities experienced by female lower limb amputees. These results have major implications for female amputees and for sex-specific research, rehabilitation, and prosthetic design.

Levy Enhanced Cross Entropy-based Optimized Training of Feedforward Neural Networks

An Artificial Neural Network (ANN) is one of the most powerful tools to predict the behavior of a system with unforeseen data. The feedforward neural network is the simplest, yet most efficient topology that is widely used in computer industries. Training of feedforward ANNs is an integral part of an ANN-based system. Typically an ANN system has inherent non-linearity with multiple parameters like weights and biases that must be optimized simultaneously. To solve such a complex optimization problem, this paper proposes the Levy Enhanced Cross Entropy (LE-CE) method. It is a population-based meta-heuristic method. In each iteration, this method produces a "distribution" of prospective solutions and updates it by updating the parameters of the distribution to obtain the optimal solutions, unlike traditional meta-heuristic methods. As a result, it reduces the chances of getting trapped into local minima, which is the typical drawback of any AI method. To further improve the global exploration capability of the CE method, it is subjected to the Levy flight which consists of a large step length during intermediate iterations. The performance of the LE-CE method is compared with state-of-the-art optimization methods. The result shows the superiority of LE-CE. The statistical ANOVA test confirms that the proposed LE-CE is statistically superior to other algorithms.

An accurate and efficient local one-dimensional method for the 3D acoustic wave equation

Abstract We establish an accurate and efficient scheme with four-order accuracy for solving three-dimensional (3D) acoustic wave equation. First, the local one-dimensional method is used to transfer the 3D wave equation into three one-dimensional wave equations. Then, a new scheme is obtained by the Padé formulas for computation of spatial second derivatives and the correction of the truncation error remainder for discretization of temporal second derivative. It is compact and can be solved directly by the Thomas algorithm. Subsequently, the Fourier analysis method and the Lax equivalence theorem are employed to prove the stability and convergence of the present scheme, which shows that it is conditionally stable and convergent, and the stability condition is superior to that of most existing numerical methods of equivalent order of accuracy in the literature. It allows us to reduce computational cost with relatively large time step lengths. Finally, numerical examples have demonstrated high accuracy, stability, and efficiency of our method.

Living on fire: Deactivating fire coral polyps for larval settlement and symbiosis in the fire coral-associated barnacle Wanella milleporae (Thoracicalcarea: Wanellinae).

Symbiosis is increasingly recognized as being an important component in marine systems, and many such relationships are initiated when free‐swimming larvae of one partner settle and become sedentary on a host partner. Therefore, several crucial questions emerge such as the larva’s mechanism of locating a host, selection of substratum and finally settlement on the surface of its future partner. Here, we investigated these mechanisms by studying how larvae of the fire coral‐associated barnacle Wanella milleporae move, settle and establish symbiosis with their host, Millepora tenera. Cyprids of W. milleporae possess a pair of specialized antennules with bell‐shaped attachment discs that enable them to explore and settle superficially on the hostile surface of the fire coral. Intriguingly, the stinging polyps of the fire coral remain in their respective pores when the cyprids explore the fire coral surface. Even when cyprids come into contact with the nematocysts on the extended stinging polyps during the exploratory phase, no immobilization effects against the cyprids were observed. The exploratory phase of Wanella cyprids can be divided into a sequence of wide searching (large step length and high walking speed), close searching (small step length and low speed) and inspection behavior, eventually resulting in permanent settlement and metamorphosis. After settlement, xenogeneic interactions occur between the fire coral and the newly metamorphosed juvenile barnacle. This involved tissue necrosis and regeneration in the fire coral host, leading to a callus ring structure around the juvenile barnacle, enhancing survival rate after settlement. The complex exploratory and settlement patterns and interactions documented here represent a breakthrough in coral reef symbiosis studies to show how invertebrates start symbiosis with fire corals.

Intrapopulation differences in polar bear movement and step selection patterns

BackgroundThe spatial ecology of individuals often varies within a population or species. Identifying how individuals in different classes interact with their environment can lead to a better understanding of population responses to human activities and environmental change and improve population estimates. Most inferences about polar bear (Ursus maritimus) spatial ecology are based on data from adult females due to morphological constraints on applying satellite radio collars to other classes of bears. Recent studies, however, have provided limited movement data for adult males and sub-adults of both sexes using ear-mounted and glue-on tags. We evaluated class-specific movements and step selection patterns for polar bears in the Chukchi Sea subpopulation during spring.MethodsWe developed hierarchical Bayesian models to evaluate polar bear movement (i.e., step length and directional persistence) and step selection at the scale of 4-day step lengths. We assessed differences in movement and step selection parameters among the three classes of polar bears (i.e., adult males, sub-adults, and adult females without cubs-of-the-year).ResultsAdult males had larger step lengths and less directed movements than adult females. Sub-adult movement parameters did not differ from the other classes but point estimates were most similar to adult females. We did not detect differences among polar bear classes in step selection parameters and parameter estimates were consistent with previous studies.ConclusionsOur findings support the use of estimated step selection patterns from adult females as a proxy for other classes of polar bears during spring. Conversely, movement analyses indicated that using data from adult females as a proxy for the movements of adult males is likely inappropriate. We recommend that researchers consider whether it is valid to extend inference derived from adult female movements to other classes, based on the questions being asked and the spatial and temporal scope of the data. Because our data were specific to spring, these findings highlight the need to evaluate differences in movement and step selection during other periods of the year, for which data from ear-mounted and glue-on tags are currently lacking.

Circular-linear copulae for animal movement data.

Animal movement is often modelled in discrete time, formulated in terms of steps taken between successive locations at regular time intervals. Steps are characterized by the distance between successive locations (step lengths) and changes in direction (turn angles). Animals commonly exhibit a mix of directed movements with large step lengths and turn angles near 0 when travelling between habitat patches and more wandering movements with small step lengths and uniform turn angles when foraging. Thus, step lengths and turn angles will typically be cross‐correlated.Most models of animal movement assume that step lengths and turn angles are independent, likely due to a lack of available alternatives. Here, we show how the method of copulae can be used to fit multivariate distributions that allow for correlated step lengths and turn angles.We describe several newly developed copulae appropriate for modelling animal movement data and fit these distributions to data collected on fishers (Pekania pennanti). The copulae are able to capture the inherent correlation in the data and provide a better fit than a model that assumes independence. Further, we demonstrate via simulation that this correlation can impact movement patterns (e.g. rates of dispersion overtime).We see many opportunities to extend this framework (e.g. to consider autocorrelation in step attributes) and to integrate it into existing frameworks for modelling animal movement and habitat selection. For example, copulae could be used to more accurately sample available locations when conducting habitat‐selection analyses.

Parallel optimization route promoted by accepting imperfect solutions for the global optimization of heat exchanger networks

The global optimization of heat exchanger network synthesis remains a hotspot and challenge in the field of chemical process integration. The random walk algorithm with compulsive evolution has shown good performance in avoiding entrapment in the local optima by accepting imperfect solutions with a certain mutation probability. This work first investigates the detailed effects of accepting imperfect solutions on the continuity of optimization and the efficiency of global optimization by analyzing the imperfect solutions generated in the optimization process. Then, a novel parallel optimization route is established to balance the global and local search ability by combing basic and fine-search optimization levels. Additionally, enhancing strategies promoted by accepting imperfect solutions and large step lengths are integrated into the parallel optimization route to further improve the efficiency of structure evolution and global optimization. Finally, three case studies are presented to verify the effectiveness of the proposed method and discuss the roles of each module and different module combinations in facilitating the global search. Many promising results with more structure possibilities are obtained in each case study, with the obtained optimal solutions being lower than most reported in the literature. This indicates the effectiveness of the proposed method in facilitating the structure evolution and global optimization for heat exchanger network synthesis.

Fully implicit two-phase VT-flash compositional flow simulation enhanced by multilayer nonlinear elimination

VT flash calculation, with the variable specification of volume, temperature and mole numbers, is a newly-rising alternative to the conventional PT flash calculation for phase behavior modeling. Until now, VT flash is primarily used as standalone calculation to solve phase equilibria problems and few works apply it to compositional flow simulation. In this study, an improved two-phase VT-flash compositional flow algorithm is developed with the multilayer nonlinear elimination method. Compared to the preceding works, the robustness and efficiency of the new algorithm is significantly improved as the nonlinear elimination method implicitly removes locally large nonlinearities and thus restore large step length for Newton iterations. To enhance the computational efficiency, an adaptive time stepping control is used to adjust the timestep size. Moreover, unnecessary stability tests are bypassed using a modified shadow region method, which accommodates to substantial composition change under large time steps. A number of numerical examples are presented to demonstrate the robustness and efficiency of the proposed VT-flash compositional flow algorithm with multilayer nonlinear elimination. Even though the convergence issue is not fully resolved, which roots in the nondifferentiable equilibrium pressure at phase boundary, the occurrence of time refinements is significantly reduced with the help of multilayer nonlinear elimination. It is also found that multilayer nonlinear elimination generally increases the number of Newton iterations slightly but enlarges the timestep size significantly. Thus, the overall computational efficiency of the VT-flash compositional flow simulation is enhanced under the multilayer nonlinear elimination method.

Weaker Connectivity of the Cortical Networks Is Linked with the Uncharacteristic Gait in Youth with Cerebral Palsy.

Cerebral palsy (CP) is the most prevalent pediatric neurologic impairment and is associated with major mobility deficiencies. This has led to extensive investigations of the sensorimotor network, with far less research focusing on other major networks. The aim of this study was to investigate the functional connectivity (FC) of the main sensory networks (i.e., visual and auditory) and the sensorimotor network, and to link FC to the gait biomechanics of youth with CP. Using resting-state functional magnetic resonance imaging, we first identified the sensorimotor, visual and auditory networks in youth with CP and neurotypical controls. Our analysis revealed reduced FC among the networks in the youth with CP relative to the controls. Notably, the visual network showed lower FC with both the sensorimotor and auditory networks. Furthermore, higher FC between the visual and sensorimotor cortices was associated with larger step length (r = 0.74, pFDR = 0.04) in youth with CP. These results confirm that CP is associated with functional brain abnormalities beyond the sensorimotor network, suggesting abnormal functional integration of the brain’s motor and primary sensory systems. The significant association between abnormal visuo-motor FC and gait could indicate a link with visuomotor disorders in this patient population.

Parametric Design of NC Tangency Point in Archimedes spiral Helical surface

This article based on matlab secondary development on the surface of the archimedean spiral cut NC contacts of parametric design. The generation principle of the spiral surface is described, and the processing error that may be caused by the processing method of the spiral surface is analyzed. In the case of meeting the processing requirements, a larger step length and a larger path distance are selected to calculate the tangent contact points of the spiral surface for CNC machining, and the accuracy of the contact points is verified by Matlab. Finally, a parametric design is carried out for the processing of the spiral curved surface tangent contact.

Robust gait design for a compass gait biped on slippery surfaces

Most current bipedal robots were modeled with an assumption that there is no slip between the stance foot and ground. This paper relaxes that assumption and undertakes a comprehensive study of the compass gait biped on slippery ground. It presents in detail the control of a biped that allows for foot slipping, and shows that feasible gaits fail on slippery ground for two causes: falling backward or requiring negative contact force which cannot be provided by the ground. To characterize a robust gait on slippery ground, three safety factors are proposed to measure the robustness: slip friction, falling friction and tolerance ability of slipping without falling. This study thus uses these factors to investigate independent influence of gait speed and step length on the robustness of the gait, and shows that gaits with small step length and moderate speed are robust and preferable on slippery surfaces. In contrast, gaits with large step length generally require large friction to maintain stable walking on slippery surfaces. Moreover, gaits with a backward swing foot velocity relative to the ground just before touch down are generally more robust than ones with a forward velocity. It is further shown that only one parameter in gait design determines the swing-backward feature, which can help design robust gaits. Models with varying physical parameters such as mass, leg length and position of center of mass (CoM) in each leg, are also studied to validate the universality of this result.

Effects of selectively assisting impaired subtasks of walking in chronic stroke survivors

BackgroundRecently developed controllers for robot-assisted gait training allow for the adjustment of assistance for specific subtasks (i.e. specific joints and intervals of the gait cycle that are related to common impairments after stroke). However, not much is known about possible interactions between subtasks and a better understanding of this can help to optimize (manual or automatic) assistance tuning in the future. In this study, we assessed the effect of separately assisting three commonly impaired subtasks after stroke: foot clearance (FC, knee flexion/extension during swing), stability during stance (SS, knee flexion/extension during stance) and weight shift (WS, lateral pelvis movement). For each of the assisted subtasks, we determined the influence on the performance of the respective subtask, and possible effects on other subtasks of walking and spatiotemporal gait parameters.MethodsThe robotic assistance for the FC, SS and WS subtasks was assessed in nine mildly impaired chronic stroke survivors while walking in the LOPES II gait trainer. Seven trials were performed for each participant in a randomized order: six trials in which either 20% or 80% of assistance was provided for each of the selected subtasks, and one baseline trial where the participant did not receive subtask-specific assistance. The influence of the assistance on performances (errors compared to reference trajectories) for the assisted subtasks and other subtasks of walking as well as spatiotemporal parameters (step length, width and height, swing and stance time) was analyzed.ResultsPerformances for the impaired subtasks (FC, SS and WS) improved significantly when assistance was applied for the respective subtask. Although WS performance improved when assisting this subtask, participants were not shifting their weight well towards the paretic leg. On a group level, not many effects on other subtasks and spatiotemporal parameters were found. Still, performance for the leading limb angle subtask improved significantly resulting in a larger step length when applying FC assistance.ConclusionFC and SS assistance leads to clear improvements in performance for the respective subtask, while our WS assistance needs further improvement. As effects of the assistance were mainly confined to the assisted subtasks, tuning of FC, SS and WS can be done simultaneously. Our findings suggest that there may be no need for specific, time-intensive tuning protocols (e.g. tuning subtasks after each other) in mildly impaired stroke survivors.

Kinematic comparison of support and swing techniques between elite and sub-elite athletes during the 30-m acceleration of sprint running

ABSTRACT The support and swing techniques of accelerative sprint were compared at different acceleration phases between different athlete groups using high-speed photography. Performance distinction between elite and sub-elite athletes (n = 16) was measured at steps 3, 4, 8, and 9 during a 30-m sprint run. The integral kinematic parameters of hip and knee joints were then compared between the groups. The results indicated that, in elite athletes, integral kinematic parameters such as larger step length, lower step frequency, shorter support time, and longer support distance resulted in larger horizontal velocity of the centre of gravity during the acceleration phase. However, as distance increased, this horizontal velocity increased with step length, support distance, and support time. For various kinematic parameters, the superior performance of elite athletes was mainly based on larger hip angle range and smaller knee angle of touch down. Hip angle of touchdown and toe-off of the supporting leg were important for sub-elite athletes, but training knee angle of touchdown was more suitable for improving performance in elite athletes. The present study provided theoretical reference for beginners and coaches of accelerative running technique.

Muscular Activity Modulation During Post-operative Walking With Hybrid Assistive Limb (HAL) in a Patient With Thoracic Myelopathy Due to Ossification of Posterior Longitudinal Ligament: A Case Report.

Disorders of the central nervous system sometimes cause severe sensory motor paralysis accompanied by gait impairment. Recently, there are several reports on the effectiveness of robot-assisted gait training for patients experiencing these issues. The purpose of this case report was to assess the neuromechanical effect of a wearable robot suit HAL (Hybrid Assistive Limb) during post-operative gait training in a patient with gait impairment due to compressive myelopathy caused by ossification of the posterior longitudinal ligament (OPLL). For this purpose, we compared lower limb muscular activities while the patient was walking with and without the robot through a course of treatment sessions by (i) gait phase-dependent muscle usage analysis, (ii) muscle synergy analysis, and (iii) muscle network analysis. The results show (i) enhanced activity of the extensor muscles for weight-bearing in the initial sessions by using HAL and reduced knee extensor and increased hip extensor activations for achieving larger steps and faster gait in the later sessions; (ii) involvement of a greater number of synergies during walking with HAL than without HAL; and (iii) modulated muscle network property during walking with HAL remaining until the next HAL session. The patient's gait was improved after completing HAL sessions, acquiring close to normal joint profile with greater range of joint movement, faster walking speed, and larger step length. We discuss that the muscular activity modulation during walking with HAL suggests altered control of the muscles by the central nervous system during post-operative walking. Activity-dependent sensorimotor augmentation by HAL is discussed in the context of recovery of gait control by the central nervous system. The relationship between the altered control and the achieved gait recovery requires further investigation.

Enhancing strategy promoted by large step length for the structure optimization of heat exchanger networks

Random Walk algorithm with Compulsive Evolution can simultaneously optimize the continuous (heat load) and integer (structure) variables in heat exchanger networks, by giving a random step length to heat load and setting the minimum heat load. Meanwhile, the structural mutation is allowed, as imperfect solutions may be accepted, in the low probability event that it may avoid entrapment in the local optima. Consequently, the step length influences the efficiency of both continuous and integer variables optimization significantly. Specifically, this study observes the distribution of step length during the evolution process, while analyzing its effects on the structural mutation and optimization. The observation found that a sufficiently large step length can stimulate structure optimization and enhance the efficiency of escaping local optima. On this basis, the study proposes an enhancing strategy promoted by large step length to establish a rational distribution curve of step length during the evolution while also advance the structure optimization of heat exchanger networks. Finally, the analysis of four different cases verifies the validity of the presented enhancing strategy, showing that the proposed approach promoted by large step length facilitates the structure optimization and achieves more cost-effective results, compared to other existing strategies.

A Mobile Robot Path Planning Scheme for Dynamic Environments

This paper proposes a four-direction search method for obstacle avoidance of mobile robots, and the collision energy of obstacles is modeled based on the neural network. For comparison and discussion purposes, the different invariant step lengths are tested in the static environment. To take the advantages of the large and small step lengths effectively, a variable step length method is adopted to improve the performance, such as less iteration number and lower total energy. The variable step length method is also applied to the dynamic environment to explore the real-time performance for path planning. Simulation results demonstrate the effectiveness and practicability of the presented scheme.