An Experimental Study on the Gait Patterns and Kinematics of Chinese Mitten Crabs

Despite the many studies on eight-legged animals and the importance of their mechanics of terrestrial locomotion, the mechanical energy of crabs in voluntary locomotion on uneven, unpredictable terrain surfaces has received little attention thus far. In this paper, motion video images of Chinese mitten crab （Eriocheir sinensis Milne-Edwards） locomotion on five types of terrains were recorded using a high-speed three-dimensional （3D） recording video system. The typical variables of locomotion such as gait patterns, duty factor, mechanical energy of the mass center, mass-specific write of the total mechanical power of the mass center, and percentage recovery, were analyzed. Results show that the Chinese mitten crab uses random gaits instead of the alternating tetrapod gait with the increasing terrain roughness. The duty factors of the rows of the leading legs are greater for all terrains than those of the rows of the trailing legs. On smooth terrain, the duty factors of the rows of the trailing legs are greater than that on rough terrains. Kinematic measurements and calculations reveal that similar to mammals, birds, and arthropods, the Chinese mitten crab uses two fundamental gaits to save mechanical energy： the inverted pendulum gait and the bouncing gait. The bouncing gait is the main pattern of mechanical energy conservation. The low probability of injury and energy expenditure due to adaptations to various terrains induce the Chinese mitten crab to modify the mass-specific rate of the total mechanical power of the mass center. The statistical results of percentage recovery also reveal that the Chinese mitten crab has lower energy recovery efficiency over rough terrains compared with smooth terrains.

The HITCR-I:Evaluation on a free gait generation method for the hexapod robot on irregular terrain

The purpose of this paper is to present and evaluate a method of free gait generation for HITCRI,a hexapod walking robot.The HITCR-I is designed as a modularized structure of legs that is based upon a four-bar linkage mechanism and with force sensors in the tip of legs,distributed hardware structure and a modular software structure of the control system.Based on a set of local rules between adjacent legs,finite state machine(FSM) model is built to control the coordination of legs.An automatic smooth transition of gait pattern is achieved through deriving the mathematical relation between gait pattern and locomotion parameters.The disordered inter-leg phase sequence is adjusted to a regular state smoothly and quickly by the local rules based FSM,and the gait pattern can transform automatically adapting to irregular terrain.The experiment on HITCR-I has demonstrated that it can walk through irregular terrain reliably and expeditiously with the free gait controller designed in this paper.

A Unified Motion Generation Approach for Quadruped L-S Walk and Trot Gaits Based on Linear Model Predictive Control

The goal of this paper is to develop a unified online motion generation scheme for quadruped lateral-sequence walk and trot gaits based on a linear model predictive control formulation.Specifically,the dynamics of the linear pendulum model is formulated over a predictive horizon by dimensional analysis.Through gait pattern conversion,the lateral-sequence walk and trot gaits of the quadruped can be regarded as unified biped gaits,allowing the dynamics of the linear inverted pendulum model to serve quadruped motion generation.In addition,a simple linearization of the center of pressure constraints for these quadruped gaits is developed for linear model predictive control problem.Furthermore,the motion generation problem can be solved online by quadratic programming with foothold adaptation.It is demonstrated that the proposed unified scheme can generate stable locomotion online for quadruped lateral-sequence walk and trot gaits,both in simulation and on hardware.The results show significant performance improvements compared to previous work.Moreover,the results also suggest the linearly simplified scheme has the ability to robustness against unexpected disturbances.

A Novel Gait Pattern Recognition Method Based on LSTM-CNN for Lower Limb Exoskeleton

This paper describes a novel gait pattern recognition method based on Long Short-Term Memory(LSTM)and Convolutional Neural Network(CNN)for lower limb exoskeleton.The Inertial Measurement Unit(IMU)installed on the exoskeleton to collect motion information,which is used for LSTM-CNN input.This article considers five common gait patterns,including walking,going up stairs,going down stairs,sitting down,and standing up.In the LSTM-CNN model,the LSTM layer is used to process temporal sequences and the CNN layer is used to extract features.To optimize the deep neural network structure proposed in this paper,some hyperparameter selection experiments were carried out.In addition,to verify the superiority of the proposed recognition method,the method is compared with several common methods such as LSTM,CNN and SVM.The results show that the average recognition accuracy can reach 97.78%,which has a good recognition eff ect.Finally,according to the experimental results of gait pattern switching,the proposed method can identify the switching gait pattern in time,which shows that it has good real-time performance.

The Role of Relative Spinal Motion during Feline Galloping for Speed Performance

Felines use their spinal column to increase their running speed at rapid locomotion performance. However, its motion profile behavior during fast gait locomotion has little attention. The goal of this study is to examine the relative spinal motion profile during two different galloping gait speeds. To understand this dynamic behavior trend, a dynamic motion of the feline animal （Felis catus domestica） was measured and analyzed by motion capture devices. Based on the experiments at two different galloping gaits, we observed a significant increase in speed （from 3.2 m.s-1 to 4.33 m.s-1） during the relative motion profile synchronization between the spinal （range： 118.86~ to 168.00~） and pelvic segments （range： 46.35~ to 91.13~） during the hindlimb stance phase （time interval： 0.495 s to 0.600 s）. Based on this discovery, the relative angular speed profile was applied to understand the possibility that the role of the relative motion match during high speed locomotion generates bigger ground reaction force.