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.     

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.     

Virtual Constraint Based Control of Bounding Gait of Quadruped Robots

This paper presents a control approach for bounding gait of quadruped robots by applying the concept of Virtual Constraints (VCs).A VC is a relative motion relation between two related joints imposed to the robots in terms of a specified gait,which can drive the robot to run with desired gait.To determine VCs for highly dynamic bounding gait,the limit cycle motions of the passive dynamic model of bounding gait are analyzed.The leg length and hip/shoulder angle trajectories corresponding to the limit cycles are parameterized by leg angles using 4 th-order polynomials.In order to track the calculated periodic motions,the polynomials are imposed on the robot as virtual motion constraints by a high-level state machine controller.A bounding speed feedback strategy is introduced to stabilize the robot running speed and enhance the stability.The control approach was applied to a newly designed lightweight bioinspired quadruped robot,AgiDog.The experimental results demonstrate that the robot can bound at a frequency up to 5 Hz and bound at a maximum speed of 1.2 m·s-1 in sagittal plane with a Froude number approximating to 1.     

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.     

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.     

Energy-efficient indoor search by swarms of simulated flying robots without global information

Swarms of flying robots are a promising alternative to ground-based robots for search in indoor environments with advantages such as increased speed and the ability to fly above obstacles. However, there are numerous problems that must be surmounted including limitations in available sensory and on-board processing capabilities, and low flight endurance. This paper introduces a novel strategy to coordinate a swarm of flying robots for indoor exploration that significantly increases energy efficiency. The presented algorithm is fully distributed and scalable. It relies solely on local sensing and low-bandwidth communication, and does not require absolute positioning, localisation, or explicit world-models. It assumes that flying robots can temporarily attach to the ceiling, or land on the ground for efficient surveillance over extended periods of time. To further reduce energy consumption, the swarm is incrementally deployed by launching one robot at a time. Extensive simulation experiments demonstrate that increasing the time between consecutive robot launches significantly lowers energy consumption by reducing total swarm flight time, while also decreasing collision probability. As a trade-off, however, the search time increases with increased inter-launch periods. These effects are stronger in more complex environments. The proposed localisation-free strategy provides an energy efficient search behaviour adaptable to different environments or timing constraints.     

Modelisation of an unspecialized quadruped walking mammal.

Kinematics and structural analyses were used as basic data to elaborate a dynamic quadruped model that may represent an unspecialized mammal. Hedgehogs were filmed on a treadmill with a cinefluorographic system providing trajectories of skeletal elements during locomotion. Body parameters such as limb segments mass and length, and segments centre of mass were checked from cadavers. These biological parameters were compiled in order to build a virtual quadruped robot. The robot locomotor behaviour was compared with the actual hedgehog to improve the model and to disclose the necessary changes. Apart from use in robotics, the resulting model may be useful to simulate the locomotion of extinct mammals.     

Effect of Flexible Back on Energy Absorption during Landing in Cats： A Biomechanical Investigation

Cats are characterized by their excellent landing ability. During the landing, they extend and bend their flexible backs. This study was undertaken to examine the effect of flexible back on impact attenuation. We collected kinematic and ground reaction force data from cats performing self-initiated jump down at different heights. Based on these measurements, the mechanical energy and elastic back energy were calculated. Further, we derived a beam model to predict back stiffness from the morphology of the vertebral spines. We found that cat could actively modulate the bending level of flexible back and the landing angle at different heights, making some kinetic energy be stored briefly as elastic strain energy in the back. This mechanism allows cat to reduce the kinetic energy dissipated by limbs and improve the efficiency of energy absorption. These results can provide bio- logical inspiration for the design of a flexible spine on a landing robot, and we anticipated their use in the energy absorption equipments for planetary exploration.     

Spinal stiffness increases with axial load: another stabilizing consequence of muscle action.

This paper addresses the role of lumbar spinal motion segment stiffness in spinal stability. The stability of the lumbar spine was modelled with loadings of 30 Nm or 60 Nm efforts about each of the three principal axes, together with the partial body weight above the lumbar spine. Two assumptions about motion segment stiffness were made: first the stiffness was represented by an 'equivalent beam' with constant stiffness properties; second the stiffness was updated based on the motion segment axial loading using a relationship determined experimentally from human lumbar spinal specimens tested with 0, 250 and 500 N of axial compressive preload. Two physiologically plausible muscle activation strategies were used in turn for calculating the muscle forces required for equilibrium. Stability analyses provided estimates of the minimum muscle stiffness required for stability. These critical muscle stiffness values decreased when preload effects were used in estimating spinal stiffness in all cases of loadings and muscle activation strategies, indicating that stability increased. These analytical findings emphasize that the spinal stiffness (as well as muscular stiffness) is important in maintaining spinal stability, and that the stiffness-increasing effect of 'preloading' should be taken into account in stability analyses.     

Robust and efficient walking with spring-like legs

The development of bipedal walking robots is inspired by human walking. A way of implementing walking could be performed by mimicking human leg dynamics. A fundamental model, representing human leg dynamics during walking and running, is the bipedal spring-mass model which is the basis for this paper. The aim of this study is the identification of leg parameters leading to a compromise between robustness and energy efficiency in walking. It is found that, compared to asymmetric walking, symmetric walking with flatter angles of attack reveals such a compromise. With increasing leg stiffness, energy efficiency increases continuously. However, robustness is the maximum at moderate leg stiffness and decreases slightly with increasing stiffness. Hence, an adjustable leg compliance would be preferred, which is adaptable to the environment. If the ground is even, a high leg stiffness leads to energy efficient walking. However, if external perturbations are expected, e.g. when the robot walks on uneven terrain, the leg should be softer and the angle of attack flatter. In the case of underactuated robots with constant physical springs, the leg stiffness should be larger than k = 14 in order to use the most robust gait. Soft legs, however, lack in both robustness and efficiency.     

A Parallel Actuated Pantograph Leg for High-speed Locomotion

High-speed running is one of the most important topics in the field of legged robots which requires strict constraints on structural design and control.To solve the problems of high acceleration,high energy consumption,high pace frequency and ground impact during high-speed movement,this paper presents a parallel actuated pantograph leg with an approximately decoupled configuration.The articulated leg features in light weight,high load capacity,high mechanical efficiency and structural stability.The similarity features of force and position between the control point and the foot are analyzed.The key design parameters,K1 and K2,which concern the dynamic performances,are carefully optimized by comprehensive evaluation of the leg inertia and mass within the maximum foot trajectory.A control strategy that incorporates virtual Spring Loaded Inverted Pendulum (SLIP) model and active force is also proposed to test the design.The strategy can implement highly flexible impedance without mechanical springs,which substantially simplifies the design and satisfies the variable stiffness requirements during high-speed running.The rationality of the structure and the effectiveness of the control law are validated by simulation and experiments.     

Path formation in a robot swarm

We present two swarm intelligence control mechanisms used for distributed robot path formation. In the first, the robots form linear chains. We study three variants of robot chains, which vary in the degree of motion allowed to the chain structure. The second mechanism is called vectorfield. In this case, the robots form a pattern that globally indicates the direction towards a goal or home location. We test each controller on a task that consists in forming a path between two objects which an individual robot cannot perceive simultaneously. Our simulation experiments show promising results. All the controllers are able to form paths in complex obstacle environments and exhibit very good scalability, robustness, and fault tolerance characteristics. Additionally, we observe that chains perform better for small robot group sizes, while vectorfield performs better for large groups.     

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.     

Research on the Kinematic Properties of a Sperm-Like Swimming Micro Robot

Nowadays, it has been one of the hottest topics for scientists to research the interventional micro robots operating in human lumen. In this paper, a novel sperm-like interventional swimming robot with single tail is presented. The kinematic models of the sperm-like helical swimming modes are built, and the motion principles are analyzed numerically. Positions and orientations are displayed graphically during the single-tail micro robot swims in liquid. Also, the displacements and the swimming velocities of the robot in x, y, z directions are plotted. It is shown that, when the single flexible tail screws in liquid environment, it generates both axial and radial propulsion forces, thus to cause the axial and the radial movements. In order to make the swimming micro robot more controllable, an improved sperm-like swimming intervention micro robot with four flexible tails is fabricated and characterized in pipes filled with silicone oil. Experimental results show that the sperm-like micro robot can swim efficiently. With different combinations of the tails' rotation directions, the robot can gain excellent controlled performance.     

Propulsive Velocity Optimization of 3-Joint Fish Robot Using Genetic-Hill Climbing Algorithm

Underwater robot is a new research field which is emerging quickly in recent years.Previous researches in this field focuson Remotely Operated Vehicles(ROVs),Autonomous Underwater Vehicles(AUVs),underwater manipulators,etc.Fish robot,which is a new type of underwater biomimetic robot,has attracted great attention because of its silence in moving and energyefficiency compared to conventional propeller-oriented propulsive mechanism.However,most of researches on fish robots have been carried out via empirical or experimental approaches,not based ondynamic optimality.In this paper,we proposed an analytical optimization approach which can guarantee the maximum propulsivevelocity of fish robot in the given parametric conditions.First,a dynamic model of 3-joint(4 links)carangiform fishrobot is derived,using which the influences of parameters of input torque functions,such as amplitude,frequency and phasedifference,on its velocity are investigated by simulation.Second,the maximum velocity of the fish robot is optimized bycombining Genetic Algorithm(GA)and Hill Climbing Algorithm(HCA).GA is used to generate the initial optimal parametersof the input functions of the system.Then,the parameters are optimized again by HCA to ensure that the final set of parametersis the"near"global optimization.Finally,both simulations and primitive experiments are carried out to prove the feasibility ofthe proposed method.     

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.     

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.     

Biomechanical basis of optimal scoliosis surgical correction

For an optimal approach to surgical correction of scoliosis, it was deemed desirable to biomechanically simulate the set of corrective forces applied by alternative internal fixation systems, so as to determine and apply the internal fixation system producing the best correction under safe levels of forces applied by the fixation systems to the spinal structures. To this end, we have developed, and presented here, (1) a spinal finite-element model relating the applied corrective forces to the corrected spinal configurations, (2) a method for determining the stiffness of the patient's spine prior to surgery, (3) computerized finite-element analysis simulation of alternative internal correction-fixation systems, so as to determine the most efficacious system, (4) instrumentations for surgically implementing the recommendations of the surgical simulation analysis and (5) comparisons of the model-simulated and surgically-obtained corrected spinal configurations. These procedures together constitute the biomechanical foundations of scoliosis surgical correction.