An Experimental Analysis of Overcoming Obstacle in Human Walking

In this paper, an experimental analysis of overcoming obstacle in human walking is carried out by means of a motion capture system. In the experiment, the lower body of an adult human is divided into seven segments, and three markers are pasted to each segment with the aim to obtain moving trajectory and to calculate joint variation during walking. Moreover, kinematic data in terms of displacement, velocity and acceleration are acquired as well. In addition, ground reaction forces are measured using force sensors. Based on the experimental results, features of overcoming obstacle in human walking are ana- lyzed. Experimental results show that the reason which leads to smooth walking can be identified as that the human has slight movement in the vertical direction during walking; the reason that human locomotion uses gravity effectively can be identified as that feet rotate around the toe joints during toe-off phase aiming at using gravitational potential energy to provide propulsion for swing phase. Furthermore, both normal walking gait and obstacle overcoming gait are characterized in a form that can provide necessary knowledge and useful databases for the implementation of motion planning and gait planning towards overcoming obstacle for humanoid robots.     

Kinematic models of lower limb joints for musculo-skeletal modelling and optimization in gait analysis

Kinematic models of lower limb joints have several potential applications in musculoskeletal modelling of the locomotion apparatus, including the reproduction of the natural joint motion. These models have recently revealed their value also for in vivo motion analysis experiments, where the soft-tissue artefact is a critical known problem. This arises at the interface between the skin markers and the underlying bone, and can be reduced by defining multibody kinematic models of the lower limb and by running optimization processes aimed at obtaining estimates of position and orientation of relevant bones. With respect to standard methods based on the separate optimization of each single body segment, this technique makes it also possible to respect joint kinematic constraints. Whereas the hip joint is traditionally assumed as a 3 degrees of freedom ball and socket articulation, many previous studies have proposed a number of different kinematic models for the knee and ankle joints. Some of these are rigid, while others have compliant elements. Some models have clear anatomical correspondences and include real joint constraints; other models are more kinematically oriented, these being mainly aimed at reproducing joint kinematics. This paper provides a critical review of the kinematic models reported in literature for the major lower limb joints and used for the reduction of soft-tissue artefact. Advantages and disadvantages of these models are discussed, considering their anatomical significance, accuracy of predictions, computational costs, feasibility of personalization, and other features. Their use in the optimization process is also addressed, both in normal and pathological subjects.     

A computational model for dynamic analysis of the human gait

Biomechanical models are important tools in the study of human motion. This work proposes a computational model to analyse the dynamics of lower limb motion using a kinematic chain to represent the body segments and rotational joints linked by viscoelastic elements. The model uses anthropometric parameters, ground reaction forces and joint Cardan angles from subjects to analyse lower limb motion during the gait. The model allows evaluating these data in each body plane. Six healthy subjects walked on a treadmill to record the kinematic and kinetic data. In addition, anthropometric parameters were recorded to construct the model. The viscoelastic parameter values were fitted for the model joints (hip, knee and ankle). The proposed model demonstrated that manipulating the viscoelastic parameters between the body segments could fit the amplitudes and frequencies of motion. The data collected in this work have viscoelastic parameter values that follow a normal distribution, indicating that these values are directly related to the gait pattern. To validate the model, we used the values of the joint angles to perform a comparison between the model results and previously published data. The model results show a same pattern and range of values found in the literature for the human gait motion.     

Simulation of lower limb axial arterial length change during locomotion

The effect of external forces on axial arterial wall mechanics has conventionally been regarded as secondary to hemodynamic influences. However, arteries are similar to muscles in terms of the manner in which they traverse joints, and their three-dimensional geometrical requirements for joint motion. This study considers axial arterial shortening and elongation due to motion of the lower extremity during gait, ascending stairs, and sitting-to-standing motion. Arterial length change was simulated by means of a graphics based anatomic and kinematic model of the lower extremity. This model estimated the axial shortening to be as much as 23% for the femoropopliteal arterial region and as much as 21% for the iliac artery. A strong correlation was observed between femoropopliteal artery shortening and maximum knee flexion angle (r2=0.8) as well as iliac artery shortening and maximum hip angle flexion (r2=0.9). This implies a significant mechanical influence of locomotion on arterial behavior in addition to hemodynamics factors. Vascular tissue has high demands for axial compliance that should be considered in the pathology of atherosclerosis and the design of vascular implants.     

Locomotion Generation and Motion Library Design for an Anguilliform Robotic Fish

In this paper, modeling, locomotion generation, motion library design and path planning for a real prototype of an Anguilliform robotic fish are presented. The robotic fish consists of four links and three joints, and the driving forces are the torques applied to the joints. Considering kinematic constraints and hydrodynamic forces, Lagrangian formulation is used to obtain the dynamic model of the fish. Using this model, three major locomotion patterns of Anguilliform fish, including forward locomotion, backward locomotion and turning locomotion are investigated. It is found that the fish exhibits different locomotion patterns by giving different reference joint angles, such as adding reversed phase difference, or adding deflections to the original reference angles. The results are validated by both simulations and experiments. Furthermore, the relations among the speed of the fish, angular frequency, undulation amplitude, phase difference, as well as the relationship between the turning radius and deflection angle are investigated. These relations provide an elaborated motion library that can be used for motion planning of the robotic fish.     

Biological Jumping Mechanism Analysis and Modeling for Frog Robot

This paper presents a mechanical model of jumping robot based on the biological mechanism analysis of frog. By biological observation and kinematic analysis the frog jump is divided into take-offphase, aerial phase and landing phase. We find the similar trajectories of hindlimb joints during jump, the important effect of foot during take-off and the role of forelimb in supporting the body. Based on the observation, the frog jump is simplified and a mechanical model is put forward. The robot leg is represented by a 4-bar spring/linkage mechanism model, which has three Degrees of Freedom （DOF） at hip joint and one DOF （passive） at tarsometatarsal joint on the foot. The shoulder and elbow joints each has one DOF for the balancing function of arm. The ground reaction force of the model is analyzed and compared with that of frog during take-off. The results show that the model has the same advantages of low likelihood of premature lift-off and high efficiency as the frog. Analysis results and the model can be employed to develop and control a robot capable of mimicking the jumping behavior of frog.     

Gait Study and Pattern Generation of a Starfish-Like Soft Robot with Flexible Rays Actuated by SMAs

This paper presents the design and development of a starfish-like soft robot with flexible rays and the implementation of multi-gait locomotion using Shape Memory Alloy （SMA） actuators. The design principle was inspired by the starfish, which possesses a remarkable symmetrical structure and soft internal skeleton. A soft robot body was constructed by using 3D printing technology. A kinematic model of the SMA spring was built and developed for motion control according to displacement and force requirements. The locomotion inspired from starfish was applied to the implementation of the multi-ray robot through the flexible actuation induced multi-gait movements in various environments. By virtue of the proposed ray control patterns in gait transition, the soft robot was able to cross over an obstacle approximately twice of its body height. Results also showed that the speed of the soft robot was 6.5 times faster on sand than on a clammy rough terrain. These experiments demonstrated that the bionic soft robot with flexible rays actuated by SMAs and multi-gait locomotion in proposed patterns can perform successfully and smoothly in various terrains.     

Dynamic analysis of load carriage biomechanics during level walking

This paper describes an investigation into the biomechanical effects of load carriage dynamics on human locomotion performance. A whole body, inverse dynamics gait model has been developed which uses only kinematic input data to define the gait cycle. To provide input data, three-dimensional gait measurements have been conducted to capture whole body motion while carrying a backpack. A nonlinear suspension model is employed to describe the backpack dynamics. The model parameters for a particular backpack system can be identified using a dynamic load carriage test-rig. Biomechanical assessments have been conducted based on combined gait and pack simulations. It was found that the backpack suspension stiffness and damping have little effect on human locomotion energetics. However, decreasing suspension stiffness offers important biomechanical advantages. The peak values of vertical pack force, acting on the trunk, and lower limb joint loads are all moderated. This would reduce shoulder strap pressures and the risk of injury when heavy loads are carried.     

Limb kinematics during locomotion in the two-toed sloth (Choloepus didactylus,Xenarthra) and its implications for the evolution of the sloth locomotor apparatus

In order to gain insight into the function of the extant sloth locomotion and its evolution, we conducted a detailed videoradiographic analysis of two-toed sloth locomotion (Xenarthra: Choloepus didactylus). Both unrestrained as well as steady-state locomotion was analyzed. Spatio-temporal gait parameters, data on interlimb coordination, and limb kinematics are reported. Two-toed sloths displayed great variability in spatio-temporal gait parameters over the observed range of speeds. They increase speed by decreasing the durations of contact and swing phases, as well as by increasing step length. Gait utilization also varies with no strict gait sequence or interlimb timing evident in slow movements, but a tendency to employ diagonal sequence, diagonal couplet gaits in fast movements. In contrast, limb kinematics were highly conserved with respect to ‘normal’ pronograde locomotion. Limb element and joint angles at touch down and lift off, element and joint excursions, and contribution to body progression of individual elements are similar to those reported for non-cursorial mammals of small to medium size. Hands and feet are specialized to maintain firm connection to supports, and do not contribute to step length or progression. In so doing, the tarsometatarsus lost its role as an individual propulsive element during the evolution of suspensory locomotion. Conservative kinematic behavior of the remaining limb elements does not preclude that muscle recruitment and neuromuscular control for limb pro- and retraction are also conserved. The observed kinematic patterns of two-toed sloths improve our understanding of the convergent evolution of quadrupedal suspensory posture and locomotion in the two extant sloth lineages.     

Effects of Pendular Waist on Gecko's Climbing: Dynamic Gait,Analytical Model and Bio-inspired Robot

Most quadruped reptiles,such as lizards,salamanders and crocodiles,swing their waists while climbing on horizontal or vertical surfaces.Accompanied by body movement,the centroid trajectory also becomes more of a zigzag path rather than a straight line.Inspired by gecko's gait and posture on a vertical surface,a gecko inspired model with one pendular waist and four active axil legs,which is called GPL model,is proposed.Relationship between the waist position,dynamic gait,and driving forces on supporting feet is analyzed.As for waist trajectory planning,a singular line between the supporting feet is found and its effects on driving forces are discussed.Based on the GPL model,it is found that a sinusoidal waist trajectory,rather than a straight line,makes the driving forces on the supporting legs smaller.Also,a waist close to the pygal can reduce the driving forces compared to the one near middle vertebration,which is in accord with gecko's body bending in the process of climbing.The principles of configuration design and gait planning are proposed based on theoretical analyses.Finally,a bio-inspired robot DracoBot is developed and both of the driving force measurements and climbing experiments reinforce theoretical analysis and the rationality of gecko's dynamic gait.     

Presenting joint kinematics of human locomotion using phase plane portraits and Poincaré maps

Additional graphical tools are needed to better visualize the joint kinematics of human locomotion. Standard plots in which the joint displacements are plotted against time or percent gait cycle do not provide sufficient information about the dynamics of the system. In this article, a study based on the two graphical tools of nonlinear dynamics to visualize the steady-state kinematics of human gait is presented. An experimental setup was developed to acquire the necessary data for application of the techniques. Twenty young adults, whose medical histories are free of gait pathology, were tested. Computerized electrogoniometers and foot switches were used to measure the kinematic data of the lower extremities and capture four instants of the gait cycle: heel strike, foot flat, heel off, and toe off. Phase plane portraits of each joint were constructed for the sagittal plane by plotting angular velocity against angular displacement. Poincaré maps were obtained by periodically sampling the joint profiles at toe off and plotting the ith iterate against the (i + 1)th one. Phase plane portraits are useful in monitoring the variations of joint velocity and position on the same graph in a more compact form. Poincaré maps are effective in differentiating steady gait from transient locomotion.     

Optimal Gait for Bioinspired Climbing Robots Using Dry Adhesion:A Quasi-Static Investigation

Legged robots relying on dry adhesives for vertical climbing are required to preload their feet against the wall to increase contact surface area and consequently maximize adhesion force. Preloading a foot causes a redistribution of forces in the entire robot, including contact forces between the other feet and the wall. An inappropriate redistribution of these forces can cause irreparable detachment of the robot from the vertical surface. This paper investigates an optimal preloading and detaching strategy that minimizes energy consumption, while retaining safety, during locomotion on vertical surfaces. The gait of a six-legged robot is planned using a quasi-static model that takes into account both the structure of the robot and the characteristics of the adhesive material. The latter was modelled from experimental data collected for this paper. A constrained optimization routine is used, and its output is a sequence of optimal posture and motor torque set-points.     

Evaluation of the kinematic parameters of normal-paced gait in subjects with gonarthrosis and the influence of gonarthrosis on the function of the ankle joint and hip joint

The aim of the study was to assess the variability of parameters characterising the gait of persons suffering from degenerative changes of the knee joint and their influence on the ankle and hip joints. The values of the angular changes in the knee, ankle and hip joints in the three planes of motion were assessed. Locomotion tests were performed on 27 persons, aged between 60 and 74, using Vicon 250, the three-dimensional analysis system. The sharpest deviations from the results of the control group were revealed in the transverse and frontal planes. Degenerative knee joint disease has changed the gait stereotype causing a reduction in the economy of gonarthrosis patients' locomotion, the influence of the disease on the function of the neighbouring joints is also distinctly marked.     

Biomimetic Quadruped Robot with a Spinal Joint and Optimal Spinal Motion via Reinforcement Learning

Feline animals can run quickly using spinal joints as well as the joints that make up their four legs.This paper describes the development of a quadruped robot including a spinal joint that biomimics feline animals.The developed robot platform consists of four legs with a double 4-bar linkage type and one simplified rotary joint.In addition,Q-learning,a type of machine learning,was used to find the optimal motion profile of the spinal joint.The bounding gait was implemented on the robot system using the motion profile of the spinal joint,and it was confirmed that using the spinal joint can achieve a faster Center of Mass(CoM)forward speed than not using the spinal joint.Although the motion profile obtained through Q-learning did not exactly match the spinal angle of a feline animal,which is more multiarticular than that of the developed robot,the tendency of the actual feline animal spinal motion profile,which is sinusoidal,was similar.     

Technical issues in using robots to reproduce joint specific gait

Reproduction of the in vivo motions of joints has become possible with improvements in robot technology and in vivo measuring techniques. A motion analysis system has been used to measure the motions of the tibia and femur of the ovine stifle joint during normal gait. These in vivo motions are then reproduced with a parallel robot. To ensure that the motion of the joint is accurately reproduced and that the resulting data are reliable, the testing frame, the data acquisition system, and the effects of limitations of the testing platform need to be considered. Of the latter, the stiffness of the robot and the ability of the control system to process sequential points on the path of motion in a timely fashion for repeatable path accuracy are of particular importance. Use of the system developed will lead to a better understanding of the mechanical environment of joints and ligaments in vivo.     

Double-step registration of in vivo stereophotogrammetry with both in vitro 6-DOFs electrogoniometry and CT medical imaging

Standard registration techniques of bone morphology to motion analysis data often lead to unsatisfactory motion simulation because of discrepancies during the location of anatomical landmarks in the datasets. This paper describes an iterative registration method of a three-dimensional (3D) skeletal model with both 6 degrees-of-freedom joint kinematics and standard motion analysis data. The method is demonstrated in this paper on the lower limb. The method includes two steps. A primary registration allowed synchronization of in vitro kinematics of the knee and ankle joints using flexion/extension angles from in vivo gait analysis. Results from primary registration were then improved by a so-called advanced registration, which integrated external constraints obtained from experimental gait pre-knowledge. One cadaver specimen was analyzed to obtain both joint kinematics of knee and ankle joints using 3D electrogoniometry, and 3D bone morphology from medical imaging data. These data were registered with motion analysis data from a volunteer during the execution of locomotor tasks. Computer graphics output was implemented to visualize the results for a motion of sitting on a chair. Final registration results allowed the observation of both in vivo motion data and joint kinematics from the synchronized specimen data. The method improved interpretation of gait analysis data, thanks to the combination of realistic 3D bone models and joint mechanism. This method should be of interest both for research in gait analysis and medical education. Validation of the overall method was performed using RMS of the differences between bone poses estimated after registration and original data from motion analysis.     

Kalman smoothing improves the estimation of joint kinematics and kinetics in marker-based human gait analysis

We developed a Kalman smoothing algorithm to improve estimates of joint kinematics from measured marker trajectories during motion analysis. Kalman smoothing estimates are based on complete marker trajectories. This is an improvement over other techniques, such as the global optimisation method (GOM), Kalman filtering, and local marker estimation (LME), where the estimate at each time instant is only based on part of the marker trajectories. We applied GOM, Kalman filtering, LME, and Kalman smoothing to marker trajectories from both simulated and experimental gait motion, to estimate the joint kinematics of a ten segment biomechanical model, with 21 degrees of freedom. Three simulated marker trajectories were studied: without errors, with instrumental errors, and with soft tissue artefacts (STA). Two modelling errors were studied: increased thigh length and hip centre dislocation. We calculated estimation errors from the known joint kinematics in the simulation study. Compared with other techniques, Kalman smoothing reduced the estimation errors for the joint positions, by more than 50% for the simulated marker trajectories without errors and with instrumental errors. Compared with GOM, Kalman smoothing reduced the estimation errors for the joint moments by more than 35%. Compared with Kalman filtering and LME, Kalman smoothing reduced the estimation errors for the joint accelerations by at least 50%. Our simulation results show that the use of Kalman smoothing substantially improves the estimates of joint kinematics and kinetics compared with previously proposed techniques (GOM, Kalman filtering, and LME) for both simulated, with and without modelling errors, and experimentally measured gait motion.     

Motion analysis of an articulated locomotion model by video and telemetric data.

Traditional techniques of human motion analysis use markers located on body articulations. The position of each marker is extracted from each image. Temporal and kinematic analysis is given by matching these data with a reference model of the human body. However, as human skin is not rigidly linked with the skeleton, each movement causes displacements of the markers and induces uncertainty in results. Moreover, the experiments are mostly conducted in restricted laboratory conditions. The aim of our project was to develop a new method for human motion analysis which needs non-sophisticated recording devices, avoids constraints to the subject studied, and can be used in various surroundings such as stadiums or gymnasiums. Our approach consisted of identifying and locating body parts in image, without markers, by using a multi-sensory sensor. This sensor exploits both data given by a video camera delivering intensity images, and data given by a 3D sensor delivering in-depth images. Our goal, in this design, was to show up the feasibility of our approach. In any case the hardware we used could facilitate an automated motion analysis. We used a linked segment model which referred to Winter's model, and we applied our method not on a human subject but on a life size articulated locomotion model. Our approach consists of finding the posture of this articulated locomotion model in the image. By performing a telemetric image segmentation, we obtained an approximate correspondence between linked segment model position and locomotion model position. This posture was then improved by injecting segmentation results in an intensity image segmentation algorithm. Several tests were conducted with video/telemetric images taken in an outdoor surrounding with the articulated model. This real life-size model was equipped with movable joints which, in static positions, described two strides of a runner. With our fusion method, we obtained relevant limbs identification and location for most postures.