Investigation on Walking and Pacing Stability of German Shepherd Dog for Different Locomotion Speeds

The motion of three German Shepherd Dogs on a treadmill was recorded using a three-dimensional motion capture system. The locomotion speed of the dog was respectively set at 4km·h^-1, 5.5km·h^-1, 7 km·h^-1 and 8.5 km·h^-1. By processing the acquired data, the joint trajectories of the dogs＇ hind limbs were computed and a time series analysis was conducted. Joint angle-angle diagrams were obtained and the Lyapunov exponents were computed. Results show that the stability decreased when speed increased, which can be attributed to the decrease in the stance phase respect to the swing phase when speed is increased. Results also show that the dogs changed gait during the tests, namely walking in the range of 4 km·h^-1 to 7 km·h^-1 and pacing at 8.5 km·h^-1 A significant drop in stability was observed from walking to pacing.

Effect of Orientation of Fibers and Holes on the Radial Strain Amplification of Campaniform sensilla

In this paper,a structural analysis is performed to gain insights on the synergistic mechanical amplification effect thatCampaniform sensilla have when combined in an array configuration.In order to simplify the analysis performed in this preliminaryinvestigation,an array of four holes in a single orthotropic lamina is considered.Firstly,a Finite Element Method(FEM) analysis is performed to discretely assess the influence that different geometrical parameters have on the mechanicalamplification properties of the array.Secondly,an artificial neural network is used to obtain an approximated multi-dimensionalcontinuous function,which models the relationship between the geometrical parameters and the amplification properties of thearray.Thirdly,an optimization is performed to identify the geometrical parameters yielding the maximum mechanical amplification.Finally,results are validated with an additional FEM simulation performed by varying geometrical parameters in theneighborhood of the identified optimal parameters.The method proposed in this paper can be fully automated and used to solvea wide range of optimization problems aimed at identifying optimal configurations of strain sensors inspired by Campaniformsensilla.

Analysis and Design of Thermally Actuated Micro-Cantilevers for High Frequency Vibrations Using Finite Element Method

Vibrational behavior of thermally actuated cantilever micro-beams and their mechanical response at moderately high frequency under a non-harmonic periodic loading is studied in this paper. Two different configurations are considered: 1) a straight beam with two actuation layers on top and bottom which utilizes the bimorph effect to induce bending;2) a uniform beam with base excitation, where the beam is mounted on an actuator which moves it periodically at its base perpendicular to its axis. Generally, vibrating micro-cantilevers are required to oscillate at a specified frequency. In order to increase the efficiency of the system, and achieve deflections with low power consumption, geometrical features of the beams can be quantified so that the required vibrating frequency matches the natural frequencies of the beam. A parametric modal analysis is conducted on two configurations of micro-cantilever and the first natural frequency of the cantilevers as a function of geometrical parameters is extracted. To evaluate vibrational behavior and thermo-mechanical efficiency of micro-cantilevers as a function of their geometrical parameters and input power, a case study with a specified vibrating frequency is considered. Due to significant complexities in the loading conditions and thermo-mechanical behavior, this task can only be tackled via numerical methods. Selecting the geometrical parameters in order to induce resonance at the nominal frequency, non-linear time-history (transient) thermo-mechanical finite element analysis (using ANSYS) is run on each configuration to study its response to the periodic heating input. Approaches to improve the effectiveness of actuators in each configuration based on their implementation are investigated.

Bioinspired Dry Adhesive Materials and Their Application in Robotics： A Review

Dry adhesives inspired from climbing animals, such as geckos and spiders, rely on van der Waals forces to attach to the opposing surface. Biological fibrillar dry adhesives have a hierarchical structure closely resembling a tree： the surface of the skin on the animal＇s feet is covered in arrays of slender micro-fibrils, each of which supports arrays of fibrils in submicron dimensions. These nano-meter size fibrils can conform closely to the opposing surfaces to induce van der Waals interaction. Bioinspired dry adhesives have been developed in research laboratories for more than a decade. To mimic the biological fibrillar adhesives, fibrillar structures have been prepared using a variety of materials and geometrical arrangements. In this review article, the mechanism and selected fabrication methods of fibrillar adhesives are summarized for future reference in adhesive development. Robotic applications of these bioinspired adhesives are also introduced in this article. Various successful appli- cations of bioinspired fibrillar adhesives can shed light on developing smart adhesives for use in automation.

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 character- istics of the adhesive material. The latter was modelled from experimental data collected for this paper. A constrained optimi- zation routine is used, and its output is a sequence of optimal posture and motor torque set-points.

Performance of Forearm FMG and sEMG for Estimating Elbow, Forearm and Wrist Positions

The ability to track upper extremity movement during activity of daily living has the potential to facilitate the recovery of individuals with neurological or physical injuries. Hence, the use of Surface Electromyography （sEMG） signals to predict upper extremity movement is an area of interest in the research community. A less established technique, Force Myography （FMG）, which uses force sensors to detect forearm muscle contraction patterns, is also able to detect some movements of the arm. This paper investigates the comparative performance of sEMG and FMG when predicting wrist, forearm and elbow positions using signals extracted from the forearm only. Support Vector Machine （SVM） and Linear Discriminant Analysis （LDA） classifiers were used to evaluate the prediction performance of both FMG and sEMG data. Ten healthy volunteers participated in this study. Under a cross validation across a repetition evaluation scheme, the SVM classifier obtained averaged accuracies of 84.3%, 82.4% and 71.0%, respectively, for predicting elbow, forearm and wrist positions using FMG; while sEMG yielded 75.4%, 83.4% and 92.4% accuracies for predicting the same respective positions. The accuracies obtained using SVM are slightly, but statistical significantly, higher than the ones obtained using LDA. However, the trends on the classification performances between FMG and sEMG are consistent. These results also indicate that the forearm FMG pattern is highly influenced by the change of elbow position, while the forearm sEMG is less subjected to the change. Overall, both forearm FMG and sEMG techniques provide abundant information that can be utilized for tracking the upper extremity movements.

A Case Study of a Force-myography Controlled Bionic Hand Mitigating Limb Position Effect

Force Myography （FMG）, which monitors pressure or radial deformation of a limb, has recently been proposed as a po- tential alternative for naturally controlling bionic robotic prostheses. This paper presents an exploratory case study aimed at evaluating how FMG behaves when a person with amputation uses a hand prosthetic prototype. One volunteer （transradial amputation） participated in this study, which investigated two experimental cases： static and dynamic. The static case considered forearm muscle contractions in a fixed elbow and shoulder positions whereas the dynamic case included movements of the elbow and shoulder. When considering eleven different hand grips, static data showed an accuracy over 99%, and dynamic data over 86% （within-trial analysis）. The across-trial analysis, that takes into account multiple trials in the same data collection set, showed a meaningful accuracy respectively of 81% and 75% only for the reduced six grips setup. While further research is needed to increase these accuracies, the obtained results provided initial evidence that this technology could represent an in- teresting alternative that is worth exploring for controlling prosthesis.