A Soft Amphibious Voxel-Type Quadruped Robot Based on Origami Flexiball of Rhombic Dodecahedron.

The research work presents a novel voxel-type soft amphibious robot based on an assembly of origami flexiballs. The geometric and elastic constitutive models of the origami flexiball are theoretically established to elucidate its intricate deformation mechanism. Especially, the zero-energy storage phenomenon and the quasi-zero-stiffness characteristic are revealed to prove that the origami flexiball is suitable for serving as soft robotic components. As a proof of concept, fourteen origami flexiballs are interconnected to form a quadruped robot capable of walking or crawling in both underwater and terrestrial environments, including flat surfaces and sandy terrain. Its adaptability across multiple environments is enhanced by the origami polyhedra-inspired hollow structure, which naturally adjusts to underwater conditions such as hydrostatic pressure and currents, improving stability and performance. Other advantages of the voxel-type soft amphibious quadruped robot include its ease of manufacture using 3D printing with accessible soft elastic materials, ensuring rapid and cost-effective fabrication. We anticipate its potentially versatile applications, including underwater pipeline inspections, offshore maintenance, seabed exploration, ecological monitoring, and marine sample collection. By leveraging metamaterial features embodied in the origami polyhedra, the presented voxel-type soft robot exemplifies an innovative approach to achieving complex functionalities in soft robotics.

Acinonyx jubatus-Inspired Quadruped Robotics: Integrating Neural Oscillators for Enhanced Locomotion Control.

This study presents the design, simulation, and prototype creation of a quadruped robot inspired by the Acinonyx jubatus (cheetah), specifically designed to replicate its distinctive walking, trotting, and galloping locomotion patterns. Following a detailed examination of the cheetah's skeletal muscle anatomy and biomechanics, a simplified model of the robot with 12 degrees of freedom was conducted. The mathematical transformation hierarchy model was established, and direct kinematics were simulated. A bio-inspired control approach was introduced, employing a Central Pattern Generator model based on Wilson-Cowan neural oscillators for each limb, interconnected by synaptic weights. This approach assisted in the simulation of oscillatory signals for relative phases corresponding to four distinct gaits in a system-level simulation platform. The design phase was conducted using CAD software (SolidWorks 2018), resulting in a 1:3-scale robot mirroring the cheetah's actual proportions. Movement simulations were performed in a virtual mechanics software environment, leading to the construction of a prototype measuring 35.5 cm in length, 21 cm in width, 27 cm in height (when standing), and weighing approximately 2.1 kg. The experimental validation of the prototype's limb angular positions and trajectories was achieved through the image processing of video-recorded movements, demonstrating a high correlation (0.9025 to 0.9560) in joint angular positions, except for the knee joint, where a correlation of 0.7071 was noted. This comprehensive approach from theoretical analysis to practical implementation showcases the potential of bio-inspired robotics in emulating complex biological locomotion.

Biomimetic lizard robot for adapting to Martian surface terrain.

The exploration of the planet Mars still is a top priority in planetary science. The Mars surface is extensively covered with soil-like material. Current wheeled rovers on Mars have been occasionally experiencing immobilization instances in unexpectedly weak terrains. The development of Mars rovers adaptable to these terrains is instrumental in improving exploration efficiency. Inspired by locomotion of the desert lizard, this paper illustrates a biomimetic quadruped robot with structures of flexible active spine and toes. By accounting for spine lateral flexion and its coordination with four leg movements, three gaits of tripod, trot and turning are designed. The motions corresponding to the three gaits are conceptually and numerically analyzed. On the granular terrains analog to Martian surface, the gasping forces by the active toes are estimated. Then traversing tests for the robot to move on Martian soil surface analog with the three gaits were investigated. Moreover, the traversing characteristics for Martian rocky and slope surface analog are analyzed. Results show that the robot can traverse Martian soil surface analog with maximum forward speed 28.13 m s-1turning speed 1.94° s-1and obstacle height 74.85 mm. The maximum angle for climbing Martian soil slope analog is 28°, corresponding slippery rate 76.8%. It is predicted that this robot can adapt to Martian granular rough terrain with gentle slopes.

Continual Reinforcement Learning for Quadruped Robot Locomotion.

The ability to learn continuously is crucial for a robot to achieve a high level of intelligence and autonomy. In this paper, we consider continual reinforcement learning (RL) for quadruped robots, which includes the ability to continuously learn sub-sequential tasks (plasticity) and maintain performance on previous tasks (stability). The policy obtained by the proposed method enables robots to learn multiple tasks sequentially, while overcoming both catastrophic forgetting and loss of plasticity. At the same time, it achieves the above goals with as little modification to the original RL learning process as possible. The proposed method uses the Piggyback algorithm to select protected parameters for each task, and reinitializes the unused parameters to increase plasticity. Meanwhile, we encourage the policy network exploring by encouraging the entropy of the soft network of the policy network. Our experiments show that traditional continual learning algorithms cannot perform well on robot locomotion problems, and our algorithm is more stable and less disruptive to the RL training progress. Several robot locomotion experiments validate the effectiveness of our method.

An Untethered Soft Robotic Dog Standing and Fast Trotting with Jointless and Resilient Soft Legs.

Soft robots are compliant, impact resistant, and relatively safe in comparison to hard robots. However, the development of untethered soft robots is still a major challenge because soft legs cannot effectively support the power and control systems. Most untethered soft robots apply a crawling or walking gait, which limits their locomotion speed and mobility. This paper presents an untethered soft robot that can move with a bioinspired dynamic trotting gait. The robot is driven by inflatable soft legs designed on the basis of the pre-charged pneumatic (PCP) actuation principle. Experimental results demonstrate that the developed robot can trot stably with the fastest speed of 23 cm/s (0.97 body length per second) and can trot over different terrains (slope, step, rough terrain, and natural terrains). The robotic dog can hold up to a 5.5 kg load in the static state and can carry up to 1.5 kg in the trotting state. Without any rigid components inside the legs, the developed robotic dog exhibits resistance to large impacts, i.e., after withstanding a 73 kg adult (46 times its body mass), the robotic dog can stand up and continue its trotting gait. This innovative robotic system has great potential in equipment inspection, field exploration, and disaster rescue.

A Software Platform for Quadruped Robots with Advanced Manipulation Capabilities.

Recently, a diverse range of robots with various functionalities have become a part of our daily lives. However, these robots either lack an arm or have less capable arms, mainly used for gestures. Another characteristic of the robots is that they are wheeled-type robots, restricting their operation to even surfaces. Several software platforms proposed in prior research have often focused on quadrupedal robots equipped with manipulators. However, many of these platforms lacked a comprehensive system combining perception, navigation, locomotion, and manipulation. This research introduces a software framework for clearing household objects with a quadrupedal robot. The proposed software framework utilizes the perception of the robot's environment through sensor inputs and organizes household objects to their designated locations. The proposed framework was verified by experiments within a simulation environment resembling the conditions of the RoboCup@Home 2021-virtual competition involving variations in objects and poses, where outcomes demonstrate promising performance.

Multi-constraint spatial coupling for the body joint quadruped robot and the CPG control method on rough terrain.

Quadruped robots have frequently appeared in various situations, including wilderness rescue, planetary exploration, and nuclear power facility maintenance. The quadruped robot with an active body joint has better environmental adaptability than one without body joints. However, it is difficult to guarantee the stability of the body joint quadruped robot when walking on rough terrain. Given the above issues, this paper proposed a gait control method for the body joint quadruped robot based on multi-constraint spatial coupling (MCSC) algorithm. The body workspace of the robot is divided into three subspaces, which are solved for different gaits, and then coupled to obtain the stable workspace of the body. A multi-layer central pattern generator model based on the Hopf oscillator is built to realize the generation and switching of walk and trot gaits. Then, combined with the MCSC area of the body, the reflex adjustment strategy on different terrains is established to adjust the body's posture in real time and realize the robot's stable locomotion. Finally, the robot prototype is developed to verify the effectiveness of the control method. The simulation and experiment results show that the proposed method can reduce the offset of the swing legs and the fluctuation of the body attitude angle. Furthermore, the quadruped robot is ensured to maintain stability by dynamically modifying its body posture. The relevant result can offer a helpful reference for the control of quadruped robots in complex environments.

Task-Oriented Systematic Design of a Heavy-Duty Electrically Actuated Quadruped Robot with High Performance.

Recent technological progress is opening up practical applications for quadruped robots. In this context, comprehensive performance demands, including speed, payload, robustness, terrain adaptability, endurance, and techno-economics, are increasing. However, design conflicts inevitably exist among these performance indicators, highlighting design challenges, especially for a heavy-duty, electrically actuated quadruped robots, which are strongly constrained by motor torque density and battery energy density. Starting from task-specific holistic system thinking, in this paper, we present a novel task-oriented approach to the design of such kind of robots, incorporating hierarchical optimization and a control-in-the-loop design, while following a structured design path that effectively exploits the strengths of both heuristic and computational designs. Guided by these philosophies, we utilize heuristic design to obtain the approximate initial form of the prototype and propose a key task-oriented actuator joint configuration, utilizing commercially available components. Subsequently, we build a step-wise analytical models considering trajectory optimization and motor heat constraints for optimization of leg length and joint match parameters to achieve a compact performance requirement envelope and minimize redundancy in the construction of task-specific components. Furthermore, we construct a holistic simulation platform with a module control algorithm for typical scenarios to evaluate subsystem results and adjust design parameters iteratively, balancing conflicts and eventually achieving a reliable design specification for detailed subsystem design. Based on these strategies, we develop a heavy-duty electric prototype achieving a maximum speed of 2 m/s in trotting gait with a load weighting over 160 kg and enduring a period of 2 h. The experiment upon the prototype verifies the efficiency of the proposed approach.

Design and Motion Analysis of a Soft-Limb Robot Inspired by Bacterial Flagella.

Soft robots demonstrate an impressive ability to adapt to objects and environments. However, current soft mobile robots often use a single mode of movement. This gives soft robots good locomotion performance in specific environments but poor performance in others. In this paper, we propose a leg-wheel mechanism inspired by bacterial flagella and use it to design a leg-wheel robot. This mechanism employs a tendon-driven continuum structure to replicate the bacterial flagellar filaments, while servo and gear components mimic the action of bacterial flagellar motors. By utilizing twisting and swinging motions of the continuum structure, the robot achieves both wheeled and legged locomotion. The paper provides comprehensive descriptions and detailed kinematic analysis of the mechanism and the robot. To verify the feasibility of the robot, a prototype was implemented, and experiments were performed on legged mode, wheeled mode, and post-overturning motion. The experimental results demonstrate that the robot can achieve legged and wheeled motions. Moreover, it is also demonstrated that the robot still has mobility after overturning. This expands the applicability scenarios of the current soft mobile robot.

High-speed running quadruped robot with a multi-joint spine adopting a 1DoF closed-loop linkage.

Improving the mobility of robots is an important goal for many real-world applications and implementing an animal-like spine structure in a quadruped robot is a promising approach to achieving high-speed running. This paper proposes a feline-like multi-joint spine adopting a one-degree-of-freedom closed-loop linkage for a quadruped robot to realize high-speed running. We theoretically prove that the proposed spine structure can realize 1.5 times the horizontal range of foot motion compared to a spine structure with a single joint. Experimental results demonstrate that a robot with the proposed spine structure achieves 1.4 times the horizontal range of motion and 1.9 times the speed of a robot with a single-joint spine structure.

Open-source lower controller for twelve degrees of freedom hydraulic quadruped robot with distributed control scheme.

Nowadays, hydraulic quadruped robot shows high power density, good impact resistance and robustness in the research. The controller is the key to realize these features. This paper shows the design of an open-source single-leg controller for the hydraulic quadruped robot Spurlos using a distributed control scheme. The single-leg system of the hydraulic quadruped robot Spurlos contains three angle encoders, three servo valves and six pressure sensors, which has the same components as most single-leg systems. Through the chips designed in the controller, the signal can be received from the encoders and the sensors, meanwhile the signal can be delivered to the servo valves. The software part of the controller adopts the MBD (Model-Based Design) method, which can greatly improve the development efficiency. According to the experiments, the controller design is reasonable, stable operation, and can satisfy the requirements of the hydraulic quadruped robot for leg motion control. The controller designed in this paper provides a solution to the problem that there is no ready-made control board for hydraulic quadruped robot which have three degrees of freedom for each leg. It enables the control researches for hydraulic quadruped robots to be more easily implemented.

A Day/Night Leader-Following Method Based on Adaptive Federated Filter for Quadruped Robots.

The quadruped robots have superior adaptability to complex terrains, compared with tracked and wheeled robots. Therefore, leader-following can help quadruped robots accomplish long-distance transportation tasks. However, long-term following has to face the change of day and night as well as the presence of interference. To solve this problem, we present a day/night leader-following method for quadruped robots toward robustness and fault-tolerant person following in complex environments. In this approach, we construct an Adaptive Federated Filter algorithm framework, which fuses the visual leader-following method and the LiDAR detection algorithm based on reflective intensity. Moreover, the framework uses the Kalman filter and adaptively adjusts the information sharing factor according to the light condition. In particular, the framework uses fault detection and multisensors information to stably achieve day/night leader-following. The approach is experimentally verified on the quadruped robot SDU-150 (Shandong University, Shandong, China). Extensive experiments reveal that robots can identify leaders stably and effectively indoors and outdoors with illumination variations and unknown interference day and night.

Research on the Jumping Control Methods of a Quadruped Robot that Imitates Animals.

At present, most quadruped robots can move quickly and steadily on both flat and undulating ground; however, natural environments are complex and changeable, so it is important for a quadruped robot to be able to jump over obstacles immediately. Inspired by the jumping movement of quadruped animals, we present aerial body posture adjustment laws and generate animal-like jumping trajectories for a quadruped robot. Then, the bionic reference trajectories are optimized to build a trajectory library of a variety of jumping motions based on the kinematic and dynamic constraints of the quadruped robot. The model predictive control (MPC) method is employed by the quadruped robot to track the optimized trajectory to achieve jumping behavior. The simulations show that the quadruped robot can jump over an obstacle of 40 cm in height. The effectiveness of the animal-like jump control method is verified.

Method of Changing Running Direction of Cheetah-Inspired Quadruped Robot.

The rapid change of motion direction during running is beneficial to improving the movement flexibility of the quadruped robot, which is of great relevance to its research. How to make the robot change its motion direction during running and achieve good dynamic stability is a problem to be solved. In this paper, a method to change the running direction of the cheetah-inspired quadruped robot is proposed. Based on the analysis of the running of the cheetah, a dynamic model of the quadruped robot is established, and a two-level stability index system, including a minimum index system and a range index system, is proposed. On this basis, the objective function based on the stability index system and optimization variables, including leg landing points, trunk movement trajectory, and posture change rule, are determined. Through these constraints, the direction changes with good dynamic stability of the cheetah-inspired quadruped robot during running is realized by controlling the leg parameters. The robot will not roll over during high-speed movement. Finally, the correctness of the proposed method is proven by simulation. This paper provides a theoretical basis for the quadruped robot's rapid change of direction in running.

Analysis of Kinematic Characteristics of Saanen Goat Spine under Multi-Slope.

In order to improve the slope movement stability and flexibility of quadruped robot, a theoretical design method of a flexible spine of a robot that was based on bionics was proposed. The kinematic characteristics of the spine were analyzed under different slopes with a Saanen goat as the research object. A Qualisys track manager (QTM) gait analysis system was used to obtain the trunk movement of goats under multiple slopes, and linear time normalization (LTN) was used to calibrate and match typical gait cycles to characterize the goat locomotion gait under slopes. Firstly, the spatial angle changes of cervical thoracic vertebrae, thoracolumbar vertebrae, and lumbar vertebrae were compared and analyzed under 0°, 5°, 10°, and 15° slopes, and it was found that the rigid and flexible coupling structure between the thoraco-lumbar vertebrae played an obvious role when moving on the slope. Moreover, with the increase in slope, the movement of the spine changed to the coupling movement of thoraco-lumbar coordination movement and a flexible swing of lumbar vertebrae. Then, the Gaussian mixture model (GMM) clustering algorithm was used to analyze the changes of the thoraco-lumbar vertebrae and lumbar vertebrae in different directions. Combined with anatomical knowledge, it was found that the motion of the thoraco-lumbar vertebrae and lumbar vertebrae in the goat was mainly manifested as a left-right swing in the coronal plane. Finally, on the basis of the analysis of the maximin and variation range of the thoraco-lumbar vertebrae and lumbar vertebrae in the coronal plane, it was found that the coupling motion of the thoraco-lumbar cooperative motion and flexible swing of the lumbar vertebrae at the slope of 10° had the most significant effect on the motion stability. SSE, R2, adjusted-R2, and RMSE were used as evaluation indexes, and the general equations of the spatial fitting curve of the goat spine were obtained by curve fitting of Matlab software. Finally, Origin software was used to obtain the optimal fitting spatial equations under eight movements of the goat spine with SSE and adjusted-R2 as indexes. The research will provide an idea for the bionic spine design with variable stiffness and multi-direction flexible bending, as well as a theoretical reference for the torso design of a bionic quadruped robot.

A Mixed-Reality Tele-Operation Method for High-Level Control of a Legged-Manipulator Robot.

In recent years, legged (quadruped) robots have been subject of technological study and continuous development. These robots have a leading role in applications that require high mobility skills in complex terrain, as is the case of Search and Rescue (SAR). These robots stand out for their ability to adapt to different terrains, overcome obstacles and move within unstructured environments. Most of the implementations recently developed are focused on data collecting with sensors, such as lidar or cameras. This work seeks to integrate a 6DoF arm manipulator to the quadruped robot ARTU-R (A1 Rescue Tasks UPM Robot) by Unitree to perform manipulation tasks in SAR environments. The main contribution of this work is focused on the High-level control of the robotic set (Legged + Manipulator) using Mixed-Reality (MR). An optimization phase of the robotic set workspace has been previously developed in Matlab for the implementation, as well as a simulation phase in Gazebo to verify the dynamic functionality of the set in reconstructed environments. The first and second generation of Hololens glasses have been used and contrasted with a conventional interface to develop the MR control part of the proposed method. Manipulations of first aid equipment have been carried out to evaluate the proposed method. The main results show that the proposed method allows better control of the robotic set than conventional interfaces, improving the operator efficiency in performing robotic handling tasks and increasing confidence in decision-making. On the other hand, Hololens 2 showed a better user experience concerning graphics and latency time.

A model-based strategy for quadruped running with differentiated fore- and hind-leg morphologies.

This article introduces a model-based strategy for a quadruped robot with differentiated fore- and hind-leg ground reaction force patterns to generate animal-like running behavior. The proposed model comprises a rigid body and two eccentric spring-loaded inverted pendulum (eSLIP) legs with dampers. The eSLIP model extends the traditional SLIP model by adding a bar to offset the spring direction. The proposed two-leg eSLIP (TL-eSLIP) model's fore- and hind legs were designed to have the same offset magnitude but in opposite offset directions, producing different braking and thrusting force patterns. The TL-eSLIP model's reference leg trajectories were designed based on the fixed-point motion of the eSLIP model. Additionally, the legs were clock torque-controlled to modulate leg motion and stabilize the model to follow its natural dynamics. The model's equations for motion were derived, and the model's dynamic behavior was simulated and analyzed. The simulation results indicate that the model with leg offsets and in either trotting or pronking has differentiated leg force patterns, and it is more stable and has larger basins of attraction than the model without leg offsets. A quadruped robot was built for experimental validation. The experimental results demonstrate that the robot with differentiated legs ran with differentiated ground reaction force patterns and ran more stably than another robot with the same leg morphology.

Terrain-Perception-Free Quadrupedal Spinning Locomotion on Versatile Terrains: Modeling, Analysis, and Experimental Validation.

Dynamic quadrupedal locomotion over rough terrains reveals remarkable progress over the last few decades. Small-scale quadruped robots are adequately flexible and adaptable to traverse uneven terrains along the sagittal direction, such as slopes and stairs. To accomplish autonomous locomotion navigation in complex environments, spinning is a fundamental yet indispensable functionality for legged robots. However, spinning behaviors of quadruped robots on uneven terrain often exhibit position drifts. Motivated by this problem, this study presents an algorithmic method to enable accurate spinning motions over uneven terrain and constrain the spinning radius of the center of mass (CoM) to be bounded within a small range to minimize the drift risks. A modified spherical foot kinematics representation is proposed to improve the foot kinematic model and rolling dynamics of the quadruped during locomotion. A CoM planner is proposed to generate a stable spinning motion based on projected stability margins. Accurate motion tracking is accomplished with linear quadratic regulator (LQR) to bind the position drift during the spinning movement. Experiments are conducted on a small-scale quadruped robot and the effectiveness of the proposed method is verified on versatile terrains including flat ground, stairs, and slopes.

Bio-Inspired Take-Off Maneuver and Control in Vertical Jumping for Quadruped Robot with Manipulator.

The jumping motion of legged robots is an effective way to overcome obstacles in the rugged microgravity planetary exploration environment. At the same time, a quadruped robot with a manipulator can achieve operational tasks during movement, which is more practical. However, the additional manipulator will restrict the jumping ability of the quadruped robot due to the increase in the weight of the system, and more active degrees of freedom will increase the control complexity. To improve the jumping height of a quadruped robot with a manipulator, a bio-inspired take-off maneuver based on the coordination of upper and lower limbs is proposed in this paper. The kinetic energy and potential energy of the system are increased by driving the manipulator-end (ME) to swing upward, and the torso driven by the legs will delay reaching the required peak speed due to the additional load caused by the accelerated ME. When the acceleration of ME is less than zero, it will pull the body upward, which reduces the peak power of the leg joints. Therefore, the jumping ability of the system is improved. To realize continuous and stable jumping, a control framework based on whole-body control was established, in which the quadruped robot with a manipulator was a simplified floating seven-link model, and the hierarchical optimization was used to solve the target joint torques. This method greatly simplifies the dynamic model and is convenient for calculation. Finally, the jumping simulations in different gravity environments and a 15° slope were performed. The jump heights have all been improved after adding the arm swing, which verified the superiority of the bio-inspired take-off maneuver proposed in this paper. Furthermore, the stability of the jumping control method was testified by the continuous and stable jumping.

Adaptive Quadruped Balance Control for Dynamic Environments Using Maximum-Entropy Reinforcement Learning.

External disturbance poses the primary threat to robot balance in dynamic environments. This paper provides a learning-based control architecture for quadrupedal self-balancing, which is adaptable to multiple unpredictable scenes of external continuous disturbance. Different from conventional methods which construct analytical models which explicitly reason the balancing process, our work utilized reinforcement learning and artificial neural network to avoid incomprehensible mathematical modeling. The control policy is composed of a neural network and a Tanh Gaussian policy, which implicitly establishes the fuzzy mapping from proprioceptive signals to action commands. During the training process, the maximum-entropy method (soft actor-critic algorithm) is employed to endow the policy with powerful exploration and generalization ability. The trained policy is validated in both simulations and realistic experiments with a customized quadruped robot. The results demonstrate that the policy can be easily transferred to the real world without elaborate configurations. Moreover, although this policy is trained in merely one specific vibration condition, it demonstrates robustness under conditions that were never encountered during training.