Effects of Initial Stance of Quadruped Trotting on Walking Stability

It is very important for quadruped walking machine to keep its stability in high speed walking. It has been indicated that moment around the supporting diagonal line of quadruped in trotting gait largely influences walking stability. In this paper, moment around the supporting diagonal line of quadruped in trotting gait is modeled and its effects on body attitude are analyzed. The degree of influence varies with different initial stances of quadruped and we get the optimal initial stance of quadruped in trotting gait with maximal walking stability. Simulation results are presented. Keywords: quadruped, trotting, attitude, walking stability

Dört bacaklı robotlar için önizlemeli kontrol ile sıfır moment noktası tabanlı yürüme yörüngesi sentezi

Bacakları üzerinde hareket eden robotların engel aşma konusunda önemli avantajları söz konusudur. Özellikle dört bacaklı robotların değişken arazi yapıları üzerinde birçok uygulamaları düşünülmektedir. Bu çalışmada, dört bacaklı bir robotun düz zemin üzerinde hızlı yol almasına yönelik tırıs türü ilerleme üzerinde durulmaktadır. Sıfır Moment Noktası (SMN) karalılık kriterine ve Doğrusal Ters Sarkaç Modeli’ne (DTSM) dayalı bir yürüme referansı sentez yöntemi sunulmaktadır. Tırıs ilerleme için bir SMN referans yörüngesi önerilmiş, bu yörüngeden, önizlemeli kontrol yaklaşımı ile Robot Ağırlık Merkezi (RAM) için bir referans yörünge elde edilmiştir. Oluşturulan ağırlık merkezi yörüngesi ters kinematik yöntemi ile bacak eklemlerinin konum referanslarının hesaplanmasında kullanılmıştır. Önerilen referans sentezi yöntemi, 16 serbestlik dereceli bir robot modeli ile üç boyutlu ve tam dinamikli bir simülasyon ortamında denenmiştir. Simülasyon sonuçları sunulan yaklaşımın başarılı olduğunu göstermektedir

Quadruped locomotion reference synthesis wıth central pattern generators tuned by evolutionary algorithms

With the recent advances in sensing, actuating and communication tecnologies and in theory for control and navigation; mobile robotic platforms are seen more promising than ever. This is so for many fields ranging from search and rescue in earthquake sites to military applications. Autonomous or teleoperated land vehicles make a major class of these mobile platforms. Legged robots, with their potential virtues in obstacle avoidance and cross-country capabilities stand out for applications on rugged terrain. In the nature, there are a lot of examples where four-legged anatomy embraces both speed and climbing characteristics. This thesis is on the locomotion reference generation of quadruped robots. Reference generation plays a vital role for the success of the locomotion controller. It involves the timing of the steps and the selection of various spatial parameters. The generated references should be suitable to be followed. They should not be over-demanding to cause the robot fall by loosing its balance. Nature tells that the pattern of the steps, that is, the gait, also changes with the speed of locomotion. A well-planned reference generation algorithm should take gait transitions into account. Central Pattern Generators (CPG) are biologically-inspired tools for legged-robot locomotion reference generation. They represent one of the main stream quadruped robot locomotion synthesis approaches, along with Zero Moment Point (ZMP) based techniques and trial–and–error methods. CPGs stand out with their natural convenience for gait transitions. This is so because of the stable limit cycle behavior inhertent in their structure. However, the parameter selection and tuning of this type of reference generators is difficult. Often, trial–and–error iterations are employed to obtain suitable parameters. The background of complicated dynamics and difficulties in reference generation makes automatic tuning of CPGs an interesting area of research. A natural command for a legged robot is the speed of its locomotion. When considered from kinematics point of view, there is no unique set of walking parameters which yield a given desired speed. However, some of the solutions can be more suitable for a stable walk, whereas others may lead to instability and cause robot to fall. This thesis proposes a quadruped gait tuning method based on evolutionary methods. A velocity command is given as the input to the system. A CPG based reference generation method is employed. 3D full-dynamics locomotion simulations with a 16-degrees-of-freedom (DOF) quadruped robot model are performed to assess the fitness of artificial populations. The fitness is measured by three different cost functions. The first cost function measures the amount of support the simulated quadruped receives from torsional virtual springs and dampers opposing the changes in body orientation, whereas the second one is a measure of energy efficiency in the locomotion. The third cost function is a combination of the firs two. Tuning results with the three cost functions are obtained and compared. Cross-over and mutation mechanisms generate new populations. Simulation results verify the merits of the proposed reference generation and tuning method

Gait transition and modulation in a quadruped robot : a brainstem-like modulation approach

In this article, we propose a bio-inspired architecture for a quadruped robot that is able to initiate/stop locomotion; generate different gaits, and to easily select and switch between the different gaits according to the speed and/or the behavioral context. This improves the robot stability and smoothness while locomoting. We apply nonlinear oscillators to model Central Pattern Generators (CPGs). These generate the rhythmic locomotor movements for a quadruped robot. The generated trajectories are modulated by a tonic signal, that encodes the required activity and/or modulation. This drive signal strength is mapped onto sets of CPG parameters. By increasing the drive signal, locomotion can be elicited and velocity increased while switching to the appropriate gaits. This drive signal can be specified according to sensory information or set a priori. The system is implemented in a simulated and real AIBO robot. Results demonstrate the adequacy of the architecture to generate and modulate the required coordinated trajectories according to a velocity increase; and to smoothly and easily switch among the different motor behaviors.The authors gratefully acknowledge Keir Pearson for all the discussions and help. This work is funded by FEDER Funding supported by the Operational Program Competitive Factors COMPETE and National Funding supported by the FCT - Foundation for Science and Technology through project PTDC/EEACRO/100655/2008

Gait Parameter Tuning Using Bayesian Optimization for an Alligator Inspired Amphibious Robot

This paper reports a sample-efficient Bayesian optimization approach for tuning the locomotion parameters of an in-house developed twelve degrees of freedom alligator-inspired amphibious robot. An optimization framework is used wherein the objective is to maximize the mean robot speed obtained via physical experiments performed on terrains with varying friction and inclinations and in the aquatic environment for swimming locomotion. We obtained an improvement in the mean robot speed by a factor of up to 6.38 using the developed approach over randomly generated locomotion parameters in 15 iterations. &nbsp

Using evolutionary artificial neural networks to design hierarchical animat nervous systems.

The research presented in this thesis examines the area of control systems for robots or animats (animal-like robots). Existing systems have problems in that they require a great deal of manual design or are limited to performing jobs of a single type. For these reasons, a better solution is desired. The system studied here is an Artificial Nervous System (ANS) which is biologically inspired; it is arranged as a hierarchy of layers containing modules operating in parallel. The ANS model has been developed to be flexible, scalable, extensible and modular. The ANS can be implemented using any suitable technology, for many different environments. The implementation focused on the two lowest layers (the reflex and action layers) of the ANS, which are concerned with control and rhythmic movement. Both layers were realised as Artificial Neural Networks (ANN) which were created using Evolutionary Algorithms (EAs). The task of the reflex layer was to control the position of an actuator (such as linear actuators or D.C. motors). The action layer performed the task of Central Pattern Generators (CPG), which produce rhythmic patterns of activity. In particular, different biped and quadruped gait patterns were created. An original neural model was specifically developed for assisting in the creation of these time-based patterns. It is shown in the thesis that Artificial Reflexes and CPGs can be configured successfully using this technique. The Artificial Reflexes were better at generalising across different actuators, without changes, than traditional controllers. Gaits such as pace, trot, gallop and pronk were successfully created using the CPGs. Experiments were conducted to determine whether modularity in the networks had an impact. It has been demonstrated that the degree of modularization in the network influences its evolvability, with more modular networks evolving more efficiently

Multistable Phase Regulation for Robust Steady and Transitional Legged Gaits

We develop robust methods that allow specification, control, and transition of a multi-legged robot’s stepping pattern—its gait—during active locomotion over natural terrain. Resulting gaits emerge through the introduction of controllers that impose appropriately-placed repellors within the space of gaits, the torus of relative leg phases, thereby mitigating against dangerous patterns of leg timing. Moreover, these repellors are organized with respect to a natural cellular decomposition of gait space and result in limit cycles with associated basins that are well characterized by these cells, thus conferring a symbolic character upon the overall behavioral repertoire. These ideas are particularly applicable to four- and six-legged robots, for which a large variety of interesting and useful (and, in many cases, familiar) gaits exist, and whose tradeoffs between speed and reliability motivate the desire for transitioning between them during active locomotion. We provide an empirical instance of this gait regulation scheme by application to a climbing hexapod, whose “physical layer” sensor-feedback control requires adequate grasp of a climbing surface but whose closed loop control perturbs the robot from its desired gait. We document how the regulation scheme secures the desired gait and permits operator selection of different gaits as required during active climbing on challenging surfaces

A new mechanical design for legged robots to reduce energy consumption

Many legged robots have been designed and built by universities, research institutes and industry; however, few investigations regard energy consumption as a crucial design criterion. This paper presents a novel configuration for legged robots to reduce the energy consumption. The proposed leg can be either used as a single leg or easily attached to bodies with four, six and eight legs. This mechanism is a parallel four-bar linkage equipped with one active and four passive joints. In fact, the usage of the passive elements leads to simple feed-forward control paradigms. Moreover, another distinctive feature of this design is the arrangement of one-way clutches and flat springs to store the potential energy for utilizing it in the next step. A locomotion prototype of the proposed mechanical structure is built and its simulation is also presented in this paper. Comparing the results with other structures demonstrates the superiority and efficiency of this work regarding energy consumption problem.</p

Dört bacaklı robotlar için önizleme kontrolü ve sıfır moment noktası esaslı yürüyüş yörüngesi üretimi

Robota verilen görevde engel aşımı gerektiğinde bacaklı robotların geri kalan mobil robotlara göre önemli avantajları bulunmaktadır. Bu makalede dört bacaklı robotların düz bir yüzeyde yürüyüşü için bir ölçümleme üretimi yöntemi sunuldu. Bu yaklaşım sıfır moment noktası (SMN) temelli kararlılık ve doğrusal ters sarkaç modeli (DTSM) üzerinedir. Yürüyüş için SMN referans gezingeleri ileri sürülüp oradan önizleme kontorü vasıtasıyla robotun ağırlık merkezi (RAM) referansı için referans gezingeleri elde edildi. Bacak eklemlerinin pozisyonları RAM referans gezingeleri üzerine ters kinematik uygulanarak hesaplandı. Öne sürülen referans gezinge üretimi sentezi, tamamen dinamik 3 boyutlu benzetimle test edildi. Benzetimde 16 serbestlik derecesine (SD) sahip dört bacaklı robot modeli kullanıldı. Benzetim sonuçları, yürüyüş için yapılan referans üretim tekniğinin başarıya ulaştığını gösteriyor