Bio-inspired Legged Robot Research Articles

Study of Joint Symmetry in Gait Evolution for Quadrupedal Robots Using a Neural Network

Bio-inspired legged robots have the potential to traverse uneven terrains in a very efficient way. The effectiveness of the robot gait depends on the joint symmetry of the robot; variations in joint symmetries can result in different types of gaits suitable for different scenarios. In the literature, symmetric and asymmetric gaits have been synthesized for legged robots; however, no relation between the gait effectiveness and joint symmetry has been studied. In this research work, the effect of joint symmetry on the robot gait is studied. To test the suggested algorithm, spider-like robot morphology was created in a simulator. The simulation environment was set to a flat surface where the robots could be tested. The simulations were performed on the PyroSim software platform, a physics engine built on top of the Open Dynamics Engine. The quadrupedal robot was created with eight joints, and it is controlled using an artificial neural network. The artificial neural network was optimized using a genetic algorithm. Different robot symmetries were tested, i.e., diagonal joint symmetry, diagonal joint reverse symmetry, adjacent joint symmetry, adjacent joint reverse symmetry and random joint symmetry or joint asymmetry. The robot controllers for each joint symmetry were evolved for a set number of generations and the robot controllers were evaluated using a fitness function that we designed. Our results showed that symmetry in joint movement could help in generating optimal gaits for our test terrain, and joint symmetry produced gaits that were already present in nature. Moreover, our results also showed that certain joint symmetries tended to perform better than others in terms of stability, speed, and distance traveled.

Vertical Jumping by a Legged Robot With Upper and Lower Leg Bi-Articular Muscle–Tendon Complexes

The bi-articular muscle-tendon complex (MTC) in an animal's leg allows a transfer of mechanical power between adjacent joints and exertion of a large force at the toes. It is capable of storing and releasing elastic energy efficiently during motions. In our previous studies, we proposed mechanisms of the bi-articular MTC for achieving extension of the upper and lower parts of the leg and experimentally demonstrated that each mechanism allows the higher jumping motion of a legged robot. In this study, we developed a bio-inspired legged robot by integrating the upper and lower leg bi-articular MTCs and investigated the effect of their cooperative utilization on the improvement of the vertical jumping ability. A jumping motion trajectory was generated through optimization to maximize the jumping ability based on a dynamic model of the bio-inspired legged robot with these bi-articular MTCs. The simulation results of the models with and without bi-articular MTCs were compared. Finally, through jumping experiments performed by implementing the generated motion trajectory, it was confirmed that the jumping ability was improved by the cooperative utilization of those bi-articular MTCs.

Novel Method for Analyzing Flexible Locomotion Patterns of Animals by Using Polar Histogram

In general, legged robots are designed to walk with a fixed rhythmic pattern. However, most animals can adapt their limb movements while walking. It is necessary to understand the mechanism of adaptability during locomotion when designing bio-inspired legged robots. In this paper, we propose an approach to analyze the flexible locomotion pattern of animals using a polar histogram. Field crickets were used to investigate variations in leg movement of insects depending on the environment. Crickets have a tripod gait; however, their leg movement changes depending on the texture of the ground. There was a significant difference between the leg movement when walking and when swimming. Our approach can explain how animals move their legs during locomotion. This study is useful for evaluating the movements of legged robots.

Oncilla Robot: A Versatile Open-Source Quadruped Research Robot With Compliant Pantograph Legs

We present Oncilla robot, a novel mobile, quadruped legged locomotion machine. This large-cat sized, 5.1 kg robot is one of a kind of a recent, bioinspired legged robot class designed with the capability of model-free locomotion control. Animal legged locomotion in rough terrain is clearly shaped by sensor feedback systems. Results with Oncilla robot show that agile and versatile locomotion is possible without sensory signals to some extend, and tracking becomes robust when feedback control is added (Ajallooeian, 2015). By incorporating mechanical and control blueprints inspired from animals, and by observing the resulting robot locomotion characteristics, we aim to understand the contribution of individual components. Legged robots have a wide mechanical and control design parameter space, and a unique potential as research tools to investigate principles of biomechanics and legged locomotion control. But the hardware and controller design can be a steep initial hurdle for academic research. To facilitate the easy start and development of legged robots, Oncilla-robot's blueprints are available through open-source. The robot's locomotion capabilities are shown in several scenarios. Specifically, its spring-loaded pantographic leg design compensates for overdetermined body and leg postures, i.e., during turning maneuvers, locomotion outdoors, or while going up and down slopes. The robot's active degree of freedom allow tight and swift direction changes, and turns on the spot. Presented hardware experiments are conducted in an open-loop manner, with little control and computational effort. For more versatile locomotion control, Oncilla-robot can sense leg joint rotations, and leg-trunk forces. Additional sensors can be included for feedback control with an open communication protocol interface. The robot's customized actuators are designed for robust actuation, and efficient locomotion. It trots with a cost of transport of 3.2 J/(Nm), at a speed of 0.63 m s-1 (Froude number 0.25). The robot trots inclined slopes up to 10°, at 0.25 m s-1. The multi-body Webots model of Oncilla robot, and Oncilla robot's extensive software architecture enables users to design and test scenarios in simulation. Controllers can directly be transferred to the real robot. Oncilla robot's blueprints are open-source published (hardware GLP v3, software LGPL v3).

A backward control based on [formula omitted]-Hopf oscillator with decoupled parameters for smooth locomotion of bio-inspired legged robot

In order to move, animals in nature usually use a rhythmic movement which is highly stable and adaptable. Movement controlled by the central pattern generator (CPG) is a spontaneous behavior of the lower nervous center. When applying the CPG model to a multi-legged robot, the stability of the robot motion and the generation and transformation of the adaptive motion model are affected by the output of the CPG. Considering the challenges of strong coupling, complex controlling, and the difficulty of using the traditional CPG model to control the foot trajectory of the robot, a novel σ-Hopf harmonic oscillator with decoupled parameters is proposed. In order to increase the flexibility and reduce the complexity of controlling the robot, a Central Pattern based Backward Control (CPBC) method is proposed. This ensures that the gait, duty factor and frequency control of the robot can be individually controlled. By adjusting the corresponding parameters, the robot can freely transform between the different motion states. Simulation techniques, where the parameters are dynamically adjusted, are used to test the effects of this process on the robot. A bio-inspired legged robotic platform is designed and tested to verify the CPBC method.

Locomotor Sub-functions for Control of Assistive Wearable Robots.

A primary goal of comparative biomechanics is to understand the fundamental physics of locomotion within an evolutionary context. Such an understanding of legged locomotion results in a transition from copying nature to borrowing strategies for interacting with the physical world regarding design and control of bio-inspired legged robots or robotic assistive devices. Inspired from nature, legged locomotion can be composed of three locomotor sub-functions, which are intrinsically interrelated: Stance: redirecting the center of mass by exerting forces on the ground. Swing: cycling the legs between ground contacts. Balance: maintaining body posture. With these three sub-functions, one can understand, design and control legged locomotory systems with formulating them in simpler separated tasks. Coordination between locomotor sub-functions in a harmonized manner appears then as an additional problem when considering legged locomotion. However, biological locomotion shows that appropriate design and control of each sub-function simplifies coordination. It means that only limited exchange of sensory information between the different locomotor sub-function controllers is required enabling the envisioned modular architecture of the locomotion control system. In this paper, we present different studies on implementing different locomotor sub-function controllers on models, robots, and an exoskeleton in addition to demonstrating their abilities in explaining humans' control strategies.

Bioinspired legged-robot based on large deformation of flexible skeleton

In this article we present STARbot, a bioinspired legged robot capable of multiple locomotion modalities by using large deformation of its skeleton. We construct STARbot by using origami-style folding of flexible laminates. The long-term goal is to provide a robotic platform with maximum mobility on multiple surfaces. This paper particularly studies the quasistatic model of STARbot’s leg under different conditions. We describe the large elastic deformation of a leg under external force, payload, and friction by using a set of non-dimensional, nonlinear approximate equations. We developed a test mechanism that models the motion of a leg in STARbot. We augmented several foot shapes and then tested them on soft to rough grounds. Both simulation and experimental findings were in good agreement. We utilized the model to develop several scales of tri and quad STARbot. We demonstrated the capability of these robots to locomote by combining their leg deformations with their foot motions. The combination provided a design platform for an active suspension STARbot with controlled foot locomotion. This included the ability of STARbot to change size, run over obstacles, walk and slide. Furthermore, in this paper we discuss a cost effective manufacturing and production method for manufacturing STARbot.

An adaptive locomotion controller for a hexapod robot: CPG, kinematics and force feedback

Insects can perform versatile locomotion behaviors such as multiple gaits, adapting to different terrains, fast escaping, etc. However, most of the existing bio-inspired legged robots do not possess such walking ability, especially when they walk on irregular terrains. To tackle this challenge, a central pattern generator (CPG)-based locomotion control methodology is proposed, integrated with a contact force feedback function. In this approach, multiple gaits are produced by the CPG module. After passing through a post-processing circuit and a delay-line, the control signal is fed into six trajectory generators to generate predefined feet trajectories for the six legs. Then, force feedback is employed to adjust these trajectories so as to adapt the robot to rough terrains. Finally the regulated trajectories are sent to inverse kinematics modules such that the position control instructions are generated to control the actuators. In both simulations and real robot experiments, we consistently show that the robot can perform sophisticated walking patterns. What is more, the robot can use the force feedback mechanism to deal with the irregularity in rough terrain. With this mechanism, the stability and adaptability of the robot are enhanced. In conclusion, the CPG-base control is an effective approach for legged robots and the force feedback approach is able to improve walking ability of the robots, especially when they walk on irregular terrains.

Neuromechanical control for hexapedal robot walking on challenging surfaces and surface classification

The neuromechanical control principles of animal locomotion provide good insights for the development of bio-inspired legged robots for walking on challenging surfaces. Based on such principles, we developed a neuromechanical controller consisting of a modular neural network (MNN) and of virtual agonist–antagonist muscle mechanisms (VAAMs). The controller allows for variable compliant leg motions of a hexapod robot, thereby leading to energy-efficient walking on different surfaces. Without any passive mechanisms or torque and position feedback at each joint, the variable compliant leg motions are achieved by only changing the stiffness parameters of the VAAMs. In addition, six surfaces can be also classified by observing the motor signals generated by the controller. The performance of the controller is tested on a physical hexapod robot. Experimental results show that it can effectively walk on six different surfaces with the specific resistances between 9.1 and 25.0, and also classify them with high accuracy.

Analysis on the performance of the SLIP runner with nonlinear spring leg

The spring-loaded inverted pendulum(SLIP) has been widely studied in both animals and robots. Generally, the majority of the relevant theoretical studies deal with elastic leg, the linear leg length-force relationship of which is obviously conflict with the biological observations. A planar spring-mass model with a nonlinear spring leg is presented to explore the intrinsic mechanism of legged locomotion with elastic component. The leg model is formulated via decoupling the stiffness coefficient and exponent of the leg compression in order that the unified stiffness can be scaled as convex, concave as well as linear profile. The apex return map of the SLIP runner is established to investigate dynamical behavior of the fixed point. The basin of attraction and Floquet Multiplier are introduced to evaluate the self-stability and initial state sensitivity of the SLIP model with different stiffness profiles. The numerical results show that larger stiffness exponent can increase top speed of stable running and also can enlarge the size of attraction domain of the fixed point. In addition, the parameter variation is conducted to detect the effect of parameter dependency, and demonstrates that on the fixed energy level and stiffness profile, the faster running speed with larger convergence rate of the stable fixed point under small local perturbation can be achieved via decreasing the angle of attack and increasing the stiffness coefficient. The perturbation recovery test is implemented to judge the ability of the model resisting large external disturbance. The result shows that the convex stiffness performs best in enhancing the robustness of SLIP runner negotiating irregular terrain. This research sheds light on the running performance of the SLIP runner with nonlinear leg spring from a theoretical perspective, and also guides the design and control of the bio-inspired legged robot.

Sensitive dependence of the motion of a legged robot on granular media

Legged locomotion on flowing ground (e.g., granular media) is unlike locomotion on hard ground because feet experience both solid- and fluid-like forces during surface penetration. Recent bioinspired legged robots display speed relative to body size on hard ground comparable with high-performing organisms like cockroaches but suffer significant performance loss on flowing materials like sand. In laboratory experiments, we study the performance (speed) of a small (2.3 kg) 6-legged robot, SandBot, as it runs on a bed of granular media (1-mm poppy seeds). For an alternating tripod gait on the granular bed, standard gait control parameters achieve speeds at best 2 orders of magnitude smaller than the 2 body lengths/s (approximately 60 cm/s) for motion on hard ground. However, empirical adjustment of these control parameters away from the hard ground settings restores good performance, yielding top speeds of 30 cm/s. Robot speed depends sensitively on the packing fraction phi and the limb frequency omega, and a dramatic transition from rotary walking to slow swimming occurs when phi becomes small enough and/or omega large enough. We propose a kinematic model of the rotary walking mode based on generic features of penetration and slip of a curved limb in granular media. The model captures the dependence of robot speed on limb frequency and the transition between walking and swimming modes but highlights the need for a deeper understanding of the physics of granular media.

The use of compliant joints and elastic energy storage in bio-inspired legged robots

From an engineering point of view, bio-inspiration can suggest mechanisms, design and functions successfully improving the state of the art in robotics. Engineers can study scaling effects in animal locomotion in order to determine the optimal gait for a given-size robot. In this paper the design of a miniature jumping robot is presented. Inspired by small jumping animals, the robot performs catapult jumps, using an elastic energy storage and a release mechanism. Compliant forelegs are completely passive, and cushion the landing re-using part of the impact energy. The influence of compliance and elastic energy storage on performances is discussed. Spring stiffness and elongation are dimensioned according to design limitations and energy constraints, avoiding early loss of ground contact, i.e. take-off before complete leg extension.