Development of a Biomimetic Quadruped Robot

This paper presents the design and prototype of a small quadruped robot whose walking motion is realized by two piezocomposite actuators. In the design, biomimetic ideas are employed to obtain the agility of motions and sustainability of a heavy load. The design of the robot legs is inspired by the leg configuration of insects, two joints （hip and knee） of the leg enable two basic motions, lifting and stepping. The robot frame is designed to have a slope relative to the horizontal plane, which makes the robot move forward. In addition, the bounding locomotion of quadruped animals is implemented in the robot. Experiments show that the robot can carry an additional load of about 100 g and run with a fairly high velocity. The quadruped prototype can be an important step towards the goal of building an autonomous mobile robot actuated by piezocomposite actuators.     

Trot Gait Design and CPG Method for a Quadruped Robot

Developing efficient walking gaits for quadruped robots has intrigued investigators for years. Trot gait, as a fast locomotion gait, has been widely used in robot control. This paper follows the idea of the six determinants of gait and designs a trot gait for a parallel-leg quadruped robot, Baby Elephant. The walking period and step length are set as constants to maintain a relatively fast speed while changing different foot trajectories to test walking quality. Experiments show that kicking leg back improves body stability. Then, a steady and smooth trot gait is designed. Furthermore, inspired by Central Pattern Generators （CPG）, a series CPG model is proposed to achieve robust and dynamic trot gait. It is generally believed that CPG is capable of producing rhythmic movements, such as swimming, walking, and flying, even when isolated from brain and sensory inputs. The proposed CPG model, inspired by the series concept, can automatically learn the previous well-designed trot gait and reproduce it, and has the ability to change its walking frequency online as well. Experiments are done in real world to verify this method.     

Extended Evolutionary Fast Learn-to-Walk Approach for Four-Legged Robots

Robot locomotion is an active research area. In this paper we focus on the locomotion of quadruped robots. An effective walking gait of quadruped robots is mainly concerned with two key aspects, namely speed and stability. The large search space of potential parameter settings for leg joints means that hand tuning is not feasible in general. As a result walking parameters are typically determined using machine learning techniques. A major shortcoming of using machine learning techniques is the significant wear and tear of robots since many parameter combinations need to be evaluated before an optimal solution is found.This paper proposes a direct walking gait learning approach, which is specifically designed to reduce wear and tear of robot motors, joints and other hardware. In essence we provide an effective learning mechanism that leads to a solution in a faster convergence time than previous algorithms. The results demonstrate that the new learning algorithm obtains a faster convergence to the best solutions in a short run. This approach is significant in obtaining faster walking gaits which will be useful for a wide range of applications where speed and stability are important. Future work will extend our methods so that the faster convergence algorithm can be applied to a two legged humanoid and lead to less wear and tear whilst still developing a fast and stable gait.     

Velocity Control of a Bounding Quadruped via Energy Control and Vestibular Reflexes

In this paper a bio-inspired approach of velocity control for a quadruped robot running with a bounding gait on compliant legs is set up. The dynamic properties ofa sagittal plane model of the robot are investigated. By analyzing the stable fixed points based on Poincare map, we find that the energy change of the system is the main source for forward velocity adjustment. Based on the analysis of the dynamics model of the robot, a new simple linear running controller is proposed using the energy control idea, which requires minimal task level feedback and only controls both the leg torque and ending impact angle. On the other hand, the functions of mammalian vestibular reflexes are discussed, and a reflex map between forward velocity and the pitch movement is built through statistical regression analysis. Finally, a velocity controller based on energy control and vestibular reflexes is built, which has the same structure as the mammalian nervous mechanism for body posture control. The new con- troller allows the robot to run autonomously without any other auxiliary equipment and exhibits good speed adjustment capa- bility. A series simulations and experiments were set to show the good movement agility, and the feasibility and validity of the robot system.     

Control of a Quadruped Robot with Bionic Springy Legs in Trotting Gait

Legged robots have better performance on discontinuous terrain than that of wheeled robots. However, the dynamic trotting and balance control of a quadruped robot is still a challenging problem, especially when the robot has multi-joint legs. This paper presents a three-dimensional model of a quadruped robot which has 6 Degrees of Freedom （DOF） on torso and 5 DOF on each leg. On the basis of the Spring-Loaded Inverted Pendulum （SLIP） model, body control algorithm is discussed in the first place to figure out how legs work in 3D trotting. Then, motivated by the principle of joint function separation and introducing certain biological characteristics, two joint coordination approaches are developed to produce the trot and provide balance. The robot reaches the highest speed of 2.0 m.s-1, and keeps balance under 250 Kg.m.s-1 lateral disturbance in the simulations. The effectiveness of these approaches is also verified on a prototype robot which runs to 0.83 m.s-1 on the treadmill, The simulations and experiments show that legged robots have good biological properties, such as the ground reaction force, and spring-like leg behavior.     

Effect of Flexible Spine Motion on Energy Efficiency in Quadruped Running

Energy efficiency is important in the performance of quadruped robots and mammals.Flexible spine motion generally exists in quadruped mammals.This paper mainly explores the effect of flexible spinal motion on energy efficiency.Firstly,a planar simplified model of the quadruped robot with flexible spine motion is introduced and two simulation experiments are carried out.The results of simulation experiments demonstrate that both spine motion and spinal flexibility can indeed increase energy efficiency,and the curve of energy efficiency change along with spinal stiffness is acquired.So,in order to obtain higher energy efficiency,quadruped robots should have flexible spine motion.In a certain speed,there is an optimal spinal stiffness which can make energy efficiency to be the best.Secondly,a planar quadruped robot with flexible spine motion is designed and the conclusions drawn in the two simulation experiments are verified.Lastly,the third simulation experiment is carried out to explore the relationship between the optimal spinal stiffness,speed and total mass.The optimal spinal stiffness increases with both speed and total mass,which has important guiding significance for adjusting the spinal stiffness of quadruped robots to make them reach the best energy efficiency.     

An Efficient Gait-generating Method for Electrical Quadruped Robot Based on Humanoid Power Planning Approach

The research field of legged robots has always relied on the bionic robotic research,especially in locomotion regulating approaches,such as foot trajectory planning,body stability regulating and energy efficiency prompting.Minimizing energy consumption and keeping the stability of body are considered as two main characteristics of human walking.This work devotes to develop an energy-efficient gait control method for electrical quadruped robots with the inspiration of human walking pattern.Based on the mechanical power distribution trend,an efficient humanoid power redistribution approach is established for the electrical quadruped robot.Through studying the walking behavior acted by mankind,such as the foot trajectory and change of mechanical power,we believe that the proposed controller which includes the bionic foot movement trajectory and humanoid power redistribution method can be implemented on the electrical quadruped robot prototype.The stability and energy efficiency of the proposed controller are tested by the simulation and the single-leg prototype experi-ment.The results verify that the humanoid power planning approach can improve the energy efficiency of the electrical quadruped robots.     

Design Study of a Cable-based Gait Training Machine

This paper deals with a design approach of a gait training machine based on a quantitative gait analysis.The proposed training machine is composed of a body weight support device and a cable-driven parallel robot.This paper is focused on the cable-driven robot,which controls the pose of the lower limb through an orthosis placed on the patient's leg.The cable robot reproduces a normal gait movement through the motion of the orthosis.A motion capture system is used to perform the quantitative analysis of a normal gait,which will be used as an input to the inverse dynamic model of the cable robot.By means of an optimization algorithm,the optimal design parameters,which minimize the tensions in the cables,are determined.Two constraints are considered,i.e.,a non-negative tension in the cables at all times,and a free cable/end-effector collision.Once the optimal solution is computed,a power analysis is carried out in order to size the robot actuators.The proposed approach can be easily extended for the design study of a similar type of cable robots.     

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.     

Dynamic motion planning for the design of robotic gait rehabilitation

In this paper we examine a method to control the stepping motion of a paralyzed person suspended over a treadmill using a robot attached to the pelvis. A leg swing motion is created by moving the pelvis without contact with the legs. The problem is formulated as an optimal control problem for an underactuated articulated chain. The optimal control problem is converted into a discrete parameter optimization and an efficient gradient-based algorithm is used to solve it. Motion capture data from an unimpaired human subject is compared to the simulation results from the dynamic motion optimization. Our results suggest that it is feasible to drive repetitive stepping on a treadmill by a paralyzed person by assisting in torso movement alone. The optimized, pelvic motion strategies are comparable to "hip-hiking" gait strategies used by people with lower limb prostheses or hemiparesis. The resulting motions can be found at the web site http://ww.eng.uci.edu/-chwang/project/stepper/stepper.html.     

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.     

Bio-Inspired Controller for a Robot Cheetah with a Neural Mechanism Controlling Leg Muscles

The realization of a high-speed running robot is one of the most challenging problems in developing legged robots.The excellent performance of cheetahs provides inspiration for the control and mechanical design of such robots.This paper presents a three-dimensional model of a cheetah that predicts the locomotory behaviors of a running cheetah.Applying biological knowledge of the neural mechanism,we control the muscle flexion and extension during the stance phase,and control the positions of the joints in the flight phase via a PD controller to minimize complexity.The proposed control strategy is shown to achieve similar locomotion of a real cheetah.The simulation realizes good biological properties,such as the leg retraction,ground reaction force,and spring-like leg behavior.The stable bounding results show the promise of the controller in high-speed locomotion.The model can reach 2.7 m·s- 1 as the highest speed,and can accelerate from 0 to 1.5 m·s -1 in one stride cycle.A mechanical structure based on this simulation is designed to demonstrate the control approach,and the most recently developed hindlimb controlled by the proposed controller is presented in swinging-leg experiments and jump-force experiments.     

Piezoelectrically Actuated Biomimetic Self-Contained Quadruped Bounding Robot

This paper presents the development of a mesoscale self-contained quadruped mobile robot that employs two pieces ofpiezocomposite actuators for the bounding locomotion.The design of the robot leg is inspired by legged insects and animals,and the biomimetic concept is implemented in the robot in a simplified form,such that each leg of the robot has only one degreeof freedom.The lack of degree of freedom is compensated by a slope of the robot frame relative to the horizontal plane.For theimplementation of the self-contained mobile robot,a small power supply circuit is designed and installed on the robot.Experimentalresults show that the robot can locomote at about 50 mm·s^-1with the circuit on board,which can be considered as asignificant step toward the goal of building an autonomous legged robot actuated by piezoelectric actuators.     

Supervised Neural Q_learning based Motion Control for Bionic Underwater Robots

Bionic underwater robots have been a hot research area in recent years. The motion control methods for a kind of bionic underwater robot with two undulating fins are discussed in this paper. The equations of motion for the bionic underwater robot are described. To apply the reinforcement learning to the actual robot control, a Supervised Neural Q_learning (SNQL) algorithm is put forward. This algorithm is based on conventional Q_learning algorithm, but has three remarkable distinctions: (1) using a feedforward neural network to approximate the Q_function table; (2) adopting a learning sample database to speed up learning and improve the stability of learning system; (3) introducing a supervised control in the earlier stage of learning for safety and to speed up learning again. Experiments of swimming straightforward are carried out with SNQL algorithm. Results indicate that the SNQL algorithm is more effective than pure neural Q_learning or supervised control. It is a feasible approach to figure out the motion control for bionic underwater robots.     

Planning and Control for Passive Dynamics Based Walking of 3D Biped Robots

Efficient walking is one of the main goals of research on biped robots.Passive Dynamics Based Walking (PDBW) has been proven to be an efficient pattern in numerous previous approaches to 2D biped walking.The goal of this study is to develop a feasible method for the application of PDBW to 3D robots.First a hybrid control method is presented,where a previously proposed two-point-foot walking pattern is employed to generate a PDBW gait in the sagittal plane and,in the frontal plane,a systematic balance control algorithm is applied including online planning of the landing point of the swing leg and feedback control of the stance foot.Then a multi-space planning structure is proposed to implement the proposed method on a 13-link 3D robot.Related kinematics and planning details of the robot are presented.Furthermore,a simulation of the 13-link biped robot verifies that stable and highly efficient walking can be achieved by the proposed control method.In addition,a number of features of the biped walking,including the transient powers and torques of the joints are explored.     

A Biological Micro Actuator: Graded and Closed-Loop Control of Insect Leg Motion by Electrical Stimulation of Muscles

In this study, a biological microactuator was demonstrated by closed-loop motion control of the front leg of an insect (Mecynorrhina torquata, beetle) via electrical stimulation of the leg muscles. The three antagonistic pairs of muscle groups in the front leg enabled the actuator to have three degrees of freedom: protraction/retraction, levation/depression, and extension/flexion. We observed that the threshold amplitude (voltage) required to elicit leg motions was approximately 1.0 V; thus, we fixed the stimulation amplitude at 1.5 V to ensure a muscle response. The leg motions were finely graded by alternation of the stimulation frequencies: higher stimulation frequencies elicited larger leg angular displacement. A closed-loop control system was then developed, where the stimulation frequency was the manipulated variable for leg-muscle stimulation (output from the final control element to the leg muscle) and the angular displacement of the leg motion was the system response. This closed-loop control system, with an optimized proportional gain and update time, regulated the leg to set at predetermined angular positions. The average electrical stimulation power consumption per muscle group was 148 µW. These findings related to and demonstrations of the leg motion control offer promise for the future development of a reliable, low-power, biological legged machine (i.e., an insect–machine hybrid legged robot).     

Kinematic Analysis and Experimental Verification on the Locomotion of Gecko

This paper presents a kinematic analysis of the locomotion of a gecko,and experimental verification of the kinematicmodel.Kinematic analysis is important for parameter design,dynamic analysis,and optimization in biomimetic robot research.The proposed kinematic analysis can simulate,without iteration,the locomotion of gecko satisfying the constraint conditionsthat maintain the position of the contacted feet on the surface.So the method has an advantage for analyzing the climbing motionof the quadruped mechanism in a real time application.The kinematic model of a gecko consists of four legs based on 7-degreesof freedom spherical-revolute-spherical joints and two revolute joints in the waist.The motion of the kinematic model issimulated based on measurement data of each joint.The motion of the kinematic model simulates the investigated real gecko’smotion by using the experimental results.The analysis solves the forward kinematics by considering the model as a combinationof closed and open serial mechanisms under the condition that maintains the contact positions of the attached feet on the ground.The motions of each joint are validated by comparing with the experimental results.In addition to the measured gait,three othergaits are simulated based on the kinematic model.The maximum strides of each gait are calculated by workspace analysis.Theresult can be used in biomimetic robot design and motion planning.     

Analysis of the gait generation principle by a simulated quadruped model with a CPG incorporating vestibular modulation

This study aims to understand the principles of gait generation in a quadrupedal model. It is difficult to determine the essence of gait generation simply by observation of the movement of complicated animals composed of brains, nerves, muscles, etc. Therefore, we build a planar quadruped model with simplified nervous system and mechanisms, in order to observe its gaits under simulation. The model is equipped with a mathematical central pattern generator (CPG), consisting of four coupled neural oscillators, basically producing a trot pattern. The model also contains sensory feedback to the CPG, measuring the body tilt (vestibular modulation). This spontaneously gives rise to an unprogrammed lateral walk at low speeds, a transverse gallop while running, in addition to trotting at a medium speed. This is because the body oscillation exhibits a double peak per leg frequency at low speeds, no peak (little oscillation) at medium speeds, and a single peak while running. The body oscillation autonomously adjusts the phase differences between the neural oscillators via the feedback. We assume that the oscillations of the four legs produced by the CPG and the body oscillation varying according to the current speed are synchronized along with the varied phase differences to keep balance during locomotion through postural adaptation via the vestibular modulation, resulting in each gait. We succeeded in determining a single simple principle that accounts for gait transition from walking to trotting to galloping, even without brain control, complicated leg mechanisms, or a flexible trunk.     

Evolving locomotion for a 12-DOF quadruped robot in simulated environments

We demonstrate the power of evolutionary robotics (ER) by comparing to a more traditional approach its performance and cost on the task of simulated robot locomotion. A novel quadruped robot is introduced, the legs of which – each having three non-coplanar degrees of freedom – are very maneuverable. Using a simplistic control architecture and a physics simulation of the robot, gaits are designed both by hand and using a highly parallel evolutionary algorithm (EA). It is found that the EA produces, in a small fraction of the time that takes to design by hand, gaits that travel at two to four times the speed of the hand-designed one. The flexibility of this approach is demonstrated by applying it across a range of differently configured simulators.