Mode Of Locomotion Research Articles

Covariation between the shape and mineralized tissues of the rib cross section in Homo sapiens, Pan troglodytes and Sts 14.

Studying rib torsion is crucial for understanding the evolution of the hominid ribcage. Interestingly, there are variables of the rib cross section that could be associated with rib torsion and, consequently, with the morphology of the thorax. The aim of this research is to conduct a comparative study of the shape and mineralized tissues of the rib cross section in different hominids to test for significant differences and, if possible, associate them to different thoracic morphotypes. The sample consists of the rib cross sections at the midshaft taken from 10 Homo sapiens and 10 Pan troglodytes adult individuals, as well as from A. africanus Sts 14. The shape of these rib cross sections was quantified using geometric morphometrics, while the mineralized tissues were evaluated using the compartmentalization index. Subsequently, covariation between both parameters was tested by a Spearman's ρ test, a permutation test and a linear regression. Generally, P. troglodytes individuals exhibit rib cross sections that are rounder and more mineralized compared to those of H. sapiens. However, the covariation between both parameters was only observed in typical ribs (levels 3-10). Although covariation was not found in the rib cross sections of Sts 14, their parameters are closer to P. troglodytes. On the one hand, the differences observed in the rib cross sections between H. sapiens and P. troglodytes might be related to different degrees of rib torsion and, consequently, to different thoracic 3D configurations. These findings can be functionally explained by considering their distinct modes of breathing and locomotion. On the other hand, although the rib cross sections belonging to Sts 14 are more similar to those of P. troglodytes, previous publications determined that their overall morphology is closer to modern humans. This discrepancy could reflect a diversity of post-cranial adaptations in Australopithecus.

Frog limbs in deep time: is jumping locomotion at the roots of the anuran Bauplan?

AbstractThe unique body plan of frogs (Lissamphibia: Anura) has been largely conserved from at least 200 Myr, and its evolution from a more generalized tetrapod condition is still poorly understood, in part due to the scarce early fossil record of Salientia, the anuran total-group. The origin of the anuran Bauplan has been classically explained as an adaptation to jumping, but recent studies incorporating new data in a phylogenetic context have challenged the popular jumping hypothesis. Here we revisit and test this hypothesis from a paleobiological perspective by integrating limb data from a wide range of extant and fossil frogs. We first explored the evolution of limb proportions from the Jurassic to the Paleogene to understand when the present limb diversity originated and whether, and to what extent, limb proportions have been conserved over the last 200 Myr. We then inferred the locomotor capabilities of extinct species by phylogenetic flexible discriminant analysis, and from these inferences, we studied the locomotor diversity of frogs over geological time and reconstructed the ancestral state for frog-like salientians. The evolution of limb proportions is characterized by an early diversification that was underway in the Jurassic, followed by a repeated convergence over a limited area of the morphospace that was already explored by the Early Cretaceous. In agreement with this early limb diversity, the Jurassic stem species were also locomotory diverse, and their inferred locomotor modes do not support the jumping hypothesis. We propose that the patterns found herein of repeated convergent evolution of both limb proportions and locomotor capabilities over geological time hamper any attempt to confidently infer the ancestral locomotion mode and, it therefore might be time to start focusing on other hypotheses on the origin of the anuran Bauplan that are not related to locomotion.

Design and implementation of IMU-based locomotion mode recognition system on Zynq SoC

Active prostheses are becoming an increasingly viable option for lower limb amputees, as they can significantly improve their quality of life and mobility. However, to ensure a robust and effective control of these prostheses, the terrain environment must be considered. In this study, we have proposed a hardware implementation of a real-time low-latency human Locomotion Mode Recognition (LMR) system on a system on chip (SoC) platform from Xilinx, which can be customized and optimized based on the user's needs without requiring external computing resources or human intervention. The system uses a single IMU sensor placed on the shank, and includes all the stages in a LMR process, i.e. signal pre-processing, feature extraction, and terrains estimation using a MLP neural network classifier to classify five terrains (level walking, stair ascent/descent, ramp ascent/descent). To achieve a flexible and efficient hardware design, the proposed system architecture was optimized using parallelism and quantization optimization techniques. This approach has resulted in a significant performance improvement, with a processing speed 15 times faster than the PL non-optimized approach, and 4.3 times faster than the PS(-O3) optimized implementation on the same Zynq FPGA device. The proposed architecture was also validated in real time via the analog discovery device.

Type synthesis of worm-like planar tensegrity mobile robot

It is a tough task to figure out how to employ a small number of actuators to give a mobile robot multiple locomotion modes. This work suggested an unique type synthesis approach for tensegrity robots with few actuators and multi-locomotion mode by unit-splicing, focusing on robotic mechanisms and aiming at three locomotion modes that worms may realize (earthworm-like, inchworm, and tumbling locomotion). The static and deformation stability were used to screen out all of the tensegrity planar units that might achieve the desired locomotion modes. On this basis, traditional tensegrity structures are modified and springs are introduced in order to decrease the number of actuators. Then, all the tensegrity mechanisms that could be driven by two motors and realize the three locomotion modes were acquired by the splicing of units and merging of cables, and the value ranges of the parameters of robotic members that could satisfy the stability criteria were presented. Following the type synthesis results, a configuration was chosen, and a prototype was created. The experiment proved the viability of the type synthesis approach by demonstrating that the robot can implement the three locomotion modes with just two actuators.

Phase oscillator optimization eliminates jittering during transition gaits in multimodal locomotion assisted by a portable hip exoskeleton

AbstractTo be successfully used in daily life situations, exoskeletons should be effective across multimodal scenarios, including walking on various terrains, and transitions between locomotion modes such as walking-to-stop. Correct continuous gait phase estimation is essential for high-level walking assistance control. Despite the impressive advances in gait phase estimation for a variety of locomotion modes, transition gait phase estimation is rarely researched, leading to the jittering of exoskeletons during walking-to-stop transitions. We propose an optimized phase oscillator (PO-opt) that estimates the gait phase correctly during transition gaits in multimodal locomotion, which is beneficial to eliminating the jittering. In the phase plane, a lateral axis extreme difference (LAED) is adopted to classify transition gaits. The threshold of LAED for transition gaits in multimodal locomotion was preliminarily determined by simulation, which was then applied and validated in experiments. Simulation results indicated that a threshold of 15.0 was suitable for transition gaits classification during treadmill walking, free walking, and ramp ascent/descent, while results of the experiment showed that a threshold between 6.5 and 10.5 was applicable for treadmill walking, free walking, and stair ascent/descent. In particular, the jittering elimination rates for 3, 4, and 5 km/h treadmill walking were improved from 29%, 21%, and 4% (PO model) to 100%, respectively, when the threshold of LAED was set at 15.0 in PO-opt model. The results indicated a significant increase in the rate of jittering elimination when the PO-opt model was applied. The model holds great promise in real-world applications for prostheses and other types of exoskeletons.

A multi-locomotion clustered tensegrity mobile robot with fewer actuators

Mobile robots with multi locomotion modes have excellent terrain adaptability. However, traditional multi-locomotion mobile robots are usually actuated by a large number of motors, making their structures heavy and bulky. As a result, the controls become complex, the load-to-mass ratio is low, and the energy consumption is high. Inspired by the bio-mechanism of worms, a novel tensegrity-based multi-locomotion mobile robot, named TJUBot, has been designed. It is actuated by only two motors, yet it has the potential to realize three locomotion modes: earthworm-like, inchworm-like, and tumbling locomotion. The design of these three locomotion modes has been implemented based on kinematic and dynamic models, and the driving law of the two motors under each locomotion mode has been established. Notably, the robot’s locomotion has been analyzed under five different terrains. A laboratory prototype of TJUBot has been developed, and experiments demonstrate that the robot can adjust to five types of terrains using the three locomotion modes. For instance, on flat ground, it achieves a maximum velocity of 2.34 BL/min, and it can pass through confined spaces with a minimum height of 1.26 BH. Moreover, the robot can climb slopes with a maximum angle of 7°, overcome obstacles with a maximum height of 0.52 BH, and traverse gaps with a maximum width as 0.35 BL. Herein, BL and BH represent the body length and body height of the robot, respectively. In addition, TJUBot exhibits outstanding performance in terms of its load-to-mass ratio, which is measured at 5.56, and its low energy consumption of 0.69J/m, as observed in experiments. The promising results obtained from these experiments indicate that TJUBot holds significant potential for applications in multi-terrain environments.

A Shape-Changing Wheeling and Jumping Robot Using Tensegrity Wheels and Bistable Mechanism

Tensegrity structures made from rigid rods and elastic cables have unique characteristics, such as being lightweight, easy to fabricate, and high load-carrying to weight capacity. In this article, we leverage tensegrity structures as wheels for a mobile robot that can actively change its shape by expanding or collapsing the wheels. Besides the shape-changing capability, using tensegrity as wheels offers several advantages over traditional wheels of similar sizes, such as a shock-absorbing capability without added mass since tensegrity wheels are both lightweight and highly compliant. We show that a robot with two icosahedron tensegrity wheels can reduce its width from 400 to 180 mm, and simultaneously, increase its height from 75 to 95 mm by changing the expanded tensegrity wheels to collapsed disk-like ones. The tensegrity wheels enable the robot to overcome steps with heights up to 110 and 150 mm with the expanded and collapsed configuration, respectively. We establish design guidelines for robots with tensegrity wheels by analyzing the maximum step height that can be overcome by the robot and the force required to collapse the wheel. The robot can also jump onto obstacles up to 300-mm high with a bistable mechanism that can gradually store but quickly release energy. We demonstrate the robot's locomotion capability in indoor and outdoor environments, including various natural terrains, like sand, grass, rocks, ice, and snow. Our results suggest that using tensegrity structures as wheels for mobile robots can enhance their capability to overcome obstacles, traverse challenging terrains, and survive falls from heights. When combined with other locomotion modes (e.g., jumping), such shape-changing robots can have broad applications for search-and-rescue after disasters or surveillance and monitoring in unstructured environments.

A New Insect-Scale Piezoelectric Robot With Asymmetric Structure

To realize the switching of the multiple locomotion modes, a new insect-scale piezoelectric robot with asymmetric structure is proposed, fabricated, and tested. The robot prototype has a weight of 32.8 g and size of 55 mm×50 mm×20 mm. Driven by two pieces of piezoelectric ceramics, working at six vibration modes, the piezoelectric robot can realize two kinds of linear motion and four kinds of circular motion by contact friction. Performance assessments show that the robot has a maximum velocity of 155 mm/s and a minimum motion radius of 45 mm. In addition, the robot can move at a speed up to 97 mm/s (100 V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p-p</sub> ) with integrated drive device (45.7 g). The insect-scale piezoelectric robot has simple structure, but has multiple motion modes, large speed range, good output characteristics and fast response time, which provides a new idea for the design and driving of micro robot.

Performance of multiple neural networks in predicting lower limb joint moments using wearable sensors.

Joint moment measurements represent an objective biomechemical parameter in joint health assessment. Inverse dynamics based on 3D motion capture data is the current 'gold standard' to estimate joint moments. Recently, machine learning combined with data measured by wearable technologies such electromyography (EMG), inertial measurement units (IMU), and electrogoniometers (GON) has been used to enable fast, easy, and low-cost measurements of joint moments. This study investigates the ability of various deep neural networks to predict lower limb joint moments merely from IMU sensors. The performance of five different deep neural networks (InceptionTimePlus, eXplainable convolutional neural network (XCM), XCMplus, Recurrent neural network (RNNplus), and Time Series Transformer (TSTPlus)) were tested to predict hip, knee, ankle, and subtalar moments using acceleration and gyroscope measurements of four IMU sensors at the trunk, thigh, shank, and foot. Multiple locomotion modes were considered including level-ground walking, treadmill walking, stair ascent, stair descent, ramp ascent, and ramp descent. We show that XCM can accurately predict lower limb joint moments using data of only four IMUs with RMSE of 0.046 ± 0.013 Nm/kg compared to 0.064 ± 0.003 Nm/kg on average for the other architectures. We found that hip, knee, and ankle joint moments predictions had a comparable RMSE with an average of 0.069 Nm/kg, while subtalar joint moments had the lowest RMSE of 0.033 Nm/kg. The real-time feedback that can be derived from the proposed method can be highly valuable for sports scientists and physiotherapists to gain insights into biomechanics, technique, and form to develop personalized training and rehabilitation programs.

Topological solitonic macromolecules

Being ubiquitous, solitons have particle-like properties, exhibiting behaviour often associated with atoms. Bound solitons emulate dynamics of molecules, though solitonic analogues of polymeric materials have not been considered yet. Here we experimentally create and model soliton polymers, which we call “polyskyrmionomers”, built of atom-like individual solitons characterized by the topological invariant representing the skyrmion number. With the help of nonlinear optical imaging and numerical modelling based on minimizing the free energy, we reveal how topological point defects bind the solitonic quasi-atoms into polyskyrmionomers, featuring linear, branched, and other macromolecule-resembling architectures, as well as allowing for encoding data by spatial distributions of the skyrmion number. Application of oscillating electric fields activates diverse modes of locomotion and internal vibrations of these self-assembled soliton structures, which depend on symmetry of the solitonic macromolecules. Our findings suggest new designs of soliton meta matter, with a potential for the use in fundamental research and technology.

Stop, then go! Rapid acceleration offsets the costs of intermittent locomotion when turning in Florida scrub lizards.

Intermittent locomotion is a common locomotor mode in small vertebrates. Pausing is thought to aid in locating a predator or prey, enhancing crypsis, lowering energy costs, and/or maneuvering around obstacles or toward a refuge. Many lizards flee predators by turning into potential refugia and subsequently pausing, presumably to conceal themselves. Intermittent locomotion may be associated with turning by allowing an animal time to assess its surroundings and/or decreasing the likelihood of losing its footing. In this study, we quantify locomotor performance and the use of intermittent locomotion in Florida scrub lizards (Sceloporus woodi) when navigating either a 45° or 90° turn. Lizards paused in 92.91% of all trials, and yet despite pausing, instantaneous speed was not different entering or exiting the turn. This result suggests that turning comes at minimal cost to forward speed for lizards under these conditions. Pausing during a turn, however, did slow speed in the turn. Interestingly, the speed in the turn did not differ in trials with a pause before the turn versus trials without a pause. The angle of the turn also had no effect on whether lizards paused. We found that lizards increase peak acceleration following pauses to compensate for lost speed during the pause, providing a mechanism that may minimize negative fitness effects associated with slow running speeds and allow intermittent locomotion to be such a common strategy in lizards.

Dynamics of a self-propelled capsule robot in contact with different folds in the small intestine

Considering the anatomy of small intestine involving lesions, circular folds and tumours are the major sources resisting the locomotion of capsule robots. By mimicking the small-bowel tumours as cone folds, this paper presents a comparative study on the dynamics of a vibro-impact capsule robot in contact with different circular and cone folds. With the aid of GPU parallel computing and path-following techniques, extensive bifurcation and basin stability analyses are performed to identify different capsule-fold interactions and unravel the parametric influences on the robot, such as fold shape, Young’s modulus and robot’s control parameters (e.g., excitation period and amplitude). It is found that fold shape and Young’s modulus may only affect capsule’s dynamics significantly when robot’s excitation period is large. Two essential locomotion modes, a period-one motion with capsule-fold contact in the small region of excitation amplitude and a fold crossing motion in the large region of excitation amplitude, dominating the dynamics of the robot regardless of fold shape and Young’s modulus are observed. In addition, the instability mechanism of this period-one motion is revealed in detail. The numerical study presented in this work will provide a solid basis for the locomotion control of the robot when encountering different types of circular folds and small-bowel tumours. It also offers the potential of utilising robot’s dynamics for bowel cancer detection.

IKA-FLOW : A Flexible Body Overset Mesh Implementation for Fish Swimming

Simulation of inertial aquatic swimmers requires fluid structure interactions with temporal body geometry deformation. In practice, his results in a change of the computational domain boundaries that represent the ”swimmer.” These simulations are traditionally done sing body-fitted mesh and mesh morphing methods, but have drawbacks of negative cell volumes and small time-steps to account for the complex swimming motion. In contrast, the overset mesh method, also provided by OpenFOAM®, overcomes most of the drawbacks of the mesh morphing method at the expense of interpolation error. The current OpenFOAM® overset motion library only supports rigid body motion and cannot be used to resolve a body undergoing undulation. A modified motion solver is presented that allows for the complex mesh motion of an overset mesh for four body-caudal fin (BCF) virtual swimmers. The results of this solver are compared with published data of body-fitted meshes. The effect of different simulation parameters (including number of solving iterations, time delay, and temporal resolution) is investigated. Additionally, a novel simulation and comparison of the Ostraciiform locomotion mode with Anguilliform, Carangiform, and Thunniform modes are made investigating the wake, drag and lift. It is concluded that fish undulation has a marked effect on reducing lift generation. Lastly, a comparison of turbulence models (Spalart-Allmaras, k − ω SST, and k − kL − ω) at multiple Reynolds numbers shows that all three models have similar performance at lower Reynolds numbers but diverge at higher numbers.

Quadrolltor: A Reconfigurable Quadrotor With Controlled Rolling and Turning

This letter reports an aerial robot–Quadrolltor, with the ability to roll and turn. Existing bimodal quadrotors feature cylindrical rolling cages that are rotationally decoupled from the robot's main rigid body. In contrast, the proposed robot employs passively reconfigurable structures to enable the second mode of locomotion, tightly coupling the attitude of the robot to the rolling cage. The benefits are precise rolling and turning control as well as improved rolling efficiency. Experiments were conducted to comprehensively validate the hybrid locomotion. The robot leveraged the superior maneuverability in the rolling mode to take photos of the surroundings at different tilting and panning angles to construct a panoramic image. Besides, the results of the power measurements show a significant reduction in the cost of transport brought by at low speed, equating to a 15-fold extension in the operational range.

Multi-Modal Mobility Morphobot (M4) with appendage repurposing for locomotion plasticity enhancement

Robot designs can take many inspirations from nature, where there are many examples of highly resilient and fault-tolerant locomotion strategies to navigate complex terrains by recruiting multi-functional appendages. For example, birds such as Chukars and Hoatzins can repurpose wings for quadrupedal walking and wing-assisted incline running. These animals showcase impressive dexterity in employing the same appendages in different ways and generating multiple modes of locomotion, resulting in highly plastic locomotion traits which enable them to interact and navigate various environments and expand their habitat range. The robotic biomimicry of animals’ appendage repurposing can yield mobile robots with unparalleled capabilities. Taking inspiration from animals, we have designed a robot capable of negotiating unstructured, multi-substrate environments, including land and air, by employing its components in different ways as wheels, thrusters, and legs. This robot is called the Multi-Modal Mobility Morphobot, or M4 in short. M4 can employ its multi-functional components composed of several actuator types to (1) fly, (2) roll, (3) crawl, (4) crouch, (5) balance, (6) tumble, (7) scout, and (8) loco-manipulate. M4 can traverse steep slopes of up to 45 deg. and rough terrains with large obstacles when in balancing mode. M4 possesses onboard computers and sensors and can autonomously employ its modes to negotiate an unstructured environment. We present the design of M4 and several experiments showcasing its multi-modal capabilities.

Design and Ground Performance Evaluation of a Multi-Joint Wheel-Track Composite Mobile Robot for Enhanced Terrain Adaptability

The tracked-wheeled mobile robot has gained significant attention in military, agricultural, construction, and other fields due to its exceptional mobility and off-road capabilities. Therefore, it is an ideal choice for reconnaissance and exploration tasks. In this study, we proposed a multi-jointed tracked-wheeled compound mobile robot that can overcome various terrains and obstacles. Based on the characteristics of multi-jointed robots, we designed two locomotion modes for the robot to climb stairs and established the kinematics/dynamics equations for its land movement. We evaluated the robot’s stability during slope climbing, its static stability during stair climbing, and its ability to cross trenches. Based on our evaluation results, we determined the key conditions for the robot to overcome obstacles, the maximum height it can climb stairs, and the maximum width it can cross trenches. Additionally, we developed a simulation model to verify the robot’s performance in different terrains and the reliability of its stair-climbing gait. The simulation results demonstrate that our multi-jointed tracked-wheeled compound mobile robot exhibits excellent reliability and adaptability in complex terrain, indicating broad application prospects in various fields and space missions.

Taking Locomotion Mode as Prior: One Algorithm-Enabled Gait Events and Kinematics Prediction on Various Terrains

Both the discrete motion states and continuous joint kinematics are essential for controlling assistive robots under changeable environmental conditions. However, few studies investigate both the discrete and continuous motion intents. This paper is the first work to propose an end-to-end motion intent decoding method that integrates recognition of discrete locomotion modes and prediction of continuous joint kinematics and gait events. First, we propose a data-driven approach to segment the transitional periods of the adjacent locomotion modes and determine their boundaries. Second, we build a CNN-LSTM network that utilizes locomotion mode classification as the prior of joint kinematics and gait events prediction and thus decodes discrete and continuous motion intents. Finally, we evaluate our method through extensive experiments and comparisons. The proposed method for locomotion mode recognition achieves an accuracy of 98.73% for steady-state and 97.53% for transitional periods. For knee angle prediction, the method achieves the ahead-of-time prediction with NRMSE lower than 8.41%, R-value higher than 0.93, and R-square higher than 0.88 for various prediction time. For gait event prediction, it predicts the future timing of events with an error of 8.46 ms for initial contact, 32.76 ms for heel off, and 8.91 ms for toe off. This study reveals the feasibility of predicting locomotion-based kinematics and gait events on various terrains. The rich motion intents studied in this work highlight the potential of a more detailed lower-limb rehabilitation system.

Identifying Roadkill Hotspots for Mammals in the Brazilian Atlantic Forest using a Functional Group Approach.

A critical step to design wildlife mitigating measures is the identification of roadkill hotspots. However, the effectiveness of mitigations based on roadkill hotspots depends on whether spatial aggregations are recurrent over time, spatially restricted, and most importantly, shared by species with diverse ecological and functional characteristics. We used a functional group approach to map roadkill hotspots for mammalian species along the BR-101/North RJ, a major road crossing important remnants of the Brazilian Atlantic Forest. We tested if functional groups present distinct hotspot patterns, and if they converge into the same road sectors, in that case, favoring optimal mitigating actions. Roadkill rates were monitored and recorded between October/2014 and September/2018 and species were classified into six functional groups based on their home range, body size, locomotion mode, diet, and forest-dependency. Hotspots along the roads were mapped for comparison of spatial patterns between functional groups. Results demonstrated that the roadkill index varied idiosyncratically for each functional group throughout the months and that no group presented seasonality. Seven hotspots were shared by two or more functional groups, highlighting the importance of these road stretches to regional mammal fauna. Two of the stretches are associated with aquatic areas extending from one side of the road to the other, and the remaining are connected to patches of native vegetation on both sides. This work brings a promising approach, yet hardly used in ecological studies on roads to analyze roadkill dynamics, assigning more importance to ecological instead of taxonomical characteristics, normally used to identify spatiotemporal patterns.

Electrodeposited Superhydrophilic-Superhydrophobic Composites for Untethered Multi-Stimuli-Responsive Soft Millirobots.

To navigate in complex and unstructured real-world environments, soft miniature robots need to possess multiple functions, including autonomous environmental sensing, self-adaptation, and multimodal locomotion. However, to achieve multifunctionality, artificial soft robots should respond to multiple stimuli, which can be achieved by multimaterial integration using facile and flexible fabrication methods. Here, a multimaterial integration strategy for fabricating soft millirobots that uses electrodeposition to integrate two inherently non-adherable materials, superhydrophilic hydrogels and superhydrophobic elastomers, together via gel roots is proposed. This approach enables the authors to electrodeposit sodium alginate hydrogel onto a laser-induced graphene-coated elastomer, which can then be laser cut into various shapes to function as multi-stimuli-responsive soft robots (MSRs). Each MSR can respond to six different stimuli to autonomously transform their shapes, and mimic flowers, vines, mimosas, and flytraps. It is demonstrated that MSRs can climb slopes, switch locomotion modes, self-adapt between air-liquid environments, and transport cargo between different environments. This multimaterial integration strategy enables creating untethered soft millirobots that have multifunctionality, such as environmental sensing, self-propulsion, and self-adaptation, paving the way for their future operation in complex real-world environments.

Regionalization and morphological integration in the vertebral column of Eurasian small-bodied newts (Salamandridae: Lissotriton).

Serially homologous structures may have complex patterns of regionalization and morphological integration, influenced by developmental Hox gene expression and functional constraints. The vertebral column, consisting of a number of repeated, developmentally constrained, and highly integrated units-vertebrae-is such a complex serially homologous structure. Functional diversification increases regionalization and modularity of the vertebral column, particularly in mammals. For salamanders, three concepts of regionalization of the vertebral column have been proposed, recognizing one, two, or three presacral regions. Using three-dimensional geometric morphometrics on vertebra models acquired with microcomputerized tomography scanning,we explored the covariation of vertebrae in four closely related taxa of small-bodied newts in the genus Lissotriton. The data were analyzed by segmented linear regression to explore patterns of vertebral regionalization and by a two-block partial least squares method to test for morphological integration. All taxa show a morphological shift posterior to the fifth trunk vertebra, which corresponds to the two-region concept. However, morphological integration is found to be strongest in the mid-trunk. Taken jointly, these results indicate a highly integrated presacral vertebral column with a subtle two-region differentiation. The results are discussed in relation to specific functional requirements, developmental and phylogenetic constraints, and specific requirements posed by a biphasic life cycle and different locomotor modes (swimming vs. walking). Further research should be conducted on different ontogenetic stages and closely related but ecologically differentiated species.