Search Results (16)

In this study, a novel compliant ankle structure with three passive degrees of freedom for quadruped robots is presented. First, this paper introduced the bionic principle and structural implementation method of the passively compliant ankle, with a particular focus on the configuration and working principle of the elastic adjustment element. Then, the kinematic model of the ankle and mathematic model of the elastic element, comprising mechanical and pneumatic model, was established by using appropriate theory. Finally, a test rig of the ankle was carried out to verify its actual function. The research results show that: (1) The ankle structure demonstrates excellent stability, maintaining its upright posture even under unreliable foot–ground interactions. (2) Compared to traditional structure, the single-leg module incorporating the proposed design exhibits smoother forward stepping under an appropriate pre-inflation pressure, with its actual motion trajectory showing closer agreement with the planned one; (3) The parallel topology enables a notable reduction in the driving torque of each joint in the leg during motion, thereby improving the energy efficiency of robots. Full article

This paper presents the design and control of a quadruped robot equipped with a six-degree-of-freedom (6-DOF) bionic active torso based on a parallel mechanism. Inspired by the compliant and flexible torsos of quadrupedal mammals, the proposed torso structure enhances locomotion performance by enabling coordinated motion between the torso and legs. A complete kinematic model of the bionic torso and the whole body of the quadruped robot is developed. To address the variation in inertial properties caused by torso motion, a model predictive control (MPC) strategy with a variable center of mass (CoM) is proposed for integrated whole-body motion control. Comparative simulations under trot gait are conducted between rigid-torso and active-torso configurations. Results show that the active torso significantly improves gait flexibility, postural stability, and locomotion efficiency. This study provides a new approach to enhancing biomimetic locomotion in quadruped robots through active torso-leg coordination. Full article

Modern poultry and egg production is facing challenges such as dead chickens and floor eggs in cage-free housing. Precision poultry management strategies are needed to address those challenges. In this study, convolutional neural network (CNN) models and an intelligent bionic quadruped robot were used to detect floor eggs and dead chickens in cage-free housing environments. A dataset comprising 1200 images was used to develop detection models, which were split into training, testing, and validation sets in a 3:1:1 ratio. Five different CNN models were developed based on YOLOv8 and the robot’s 360° panoramic depth perception camera. The final results indicated that YOLOv8m exhibited the highest performance, achieving a precision of 90.59%. The application of the optimal model facilitated the detection of floor eggs in dimly lit areas such as below the feeder area and in corner spaces, as well as the detection of dead chickens within the flock. This research underscores the utility of bionic robotics and convolutional neural networks for poultry management and precision livestock farming. Full article

Quadruped robots, with their biomimetic structure, are capable of stable locomotion in complex terrains and are vital in rescue, exploration, and military applications. However, developing multi-modal robots that feature simple motion control while adapting to diverse amphibious environments remains a significant challenge. These robots need to excel at obstacle-crossing, waterproofing, and maintaining stability across various locomotion modes. To address these challenges, this paper introduces a novel leg–fin integrated propulsion mechanism for a bionic quadruped robot, utilizing rapidly advancing soft materials and integrated molding technologies. The robot’s motion is modeled and decomposed using an improved central pattern generator (CPG) control network. By leveraging the control characteristics of the CPG model, global control of the single-degree-of-freedom drive mechanism is achieved, allowing smooth transitions between different motion modes. The design is verified through simulations conducted in the Webots environment. Finally, a physical prototype of the quadruped compliant robot is constructed, and experiments are carried out to test its walking, turning, and obstacle-crossing abilities in various environments. The experimental results demonstrate that the robot shows a significant speed advantage in regions where land and water meet, reaching a maximum speed of 1.03 body lengths per second (bl/s). Full article

This paper presents a novel approach to developing control strategies for mobile robots, specifically the Pegasus, a bionic wheel-legged quadruped robot with unique chassis mechanics that enable four-wheel independent steering and diverse gaits. A multi-agent (MA) reinforcement learning (RL) controller is proposed, treating each leg as an independent agent with the goal of autonomous learning. The framework involves a multi-agent setup to model torso and leg dynamics, incorporating motion guidance optimization signal in the policy training and reward function. By doing so, we address leg schedule patterns for the complex configuration of the Pegasus, the requirement for various gaits, and the design of reward functions for MA-RL agents. Agents were trained using two variations of policy networks based on the framework, and real-world tests show promising results with easy policy transfer from simulation to the actual hardware. The proposed framework models acquired higher rewards and converged faster in training than other variants. Various experiments on the robot deployed framework showed fast response (0.8 s) under disturbance and low linear, angular velocity, and heading error, which was 2.5 cm/s, 0.06 rad/s, and 4°, respectively. Overall, the study demonstrates the feasibility of the proposed MA-RL control framework. Full article

This article delineates the enhancement of an autonomous navigation and obstacle avoidance system for a quadruped robot dog. Part one of this paper presents the integration of a sophisticated multi-level dynamic control framework, utilizing Model Predictive Control (MPC) and Whole-Body Control (WBC) from MIT Cheetah. The system employs an Intel RealSense D435i depth camera for depth vision-based navigation, which enables high-fidelity 3D environmental mapping and real-time path planning. A significant innovation is the customization of the EGO-Planner to optimize trajectory planning in dynamically changing terrains, coupled with the implementation of a multi-body dynamics model that significantly improves the robot’s stability and maneuverability across various surfaces. The experimental results show that the RGB-D system exhibits superior velocity stability and trajectory accuracy to the SLAM system, with a 20% reduction in the cumulative velocity error and a 10% improvement in path tracking precision. The experimental results also show that the RGB-D system achieves smoother navigation, requiring 15% fewer iterations for path planning, and a 30% faster success rate recovery in challenging environments. The successful application of these technologies in simulated urban disaster scenarios suggests promising future applications in emergency response and complex urban environments. Part two of this paper presents the development of a robust path planning algorithm for a robot dog on a rough terrain based on attached binocular vision navigation. We use a commercial-of-the-shelf (COTS) robot dog. An optical CCD binocular vision dynamic tracking system is used to provide environment information. Likewise, the pose and posture of the robot dog are obtained from the robot’s own sensors, and a kinematics model is established. Then, a binocular vision tracking method is developed to determine the optimal path, provide a proposal (commands to actuators) of the position and posture of the bionic robot, and achieve stable motion on tough terrains. The terrain is assumed to be a gentle uneven terrain to begin with and subsequently proceeds to a more rough surface. This work consists of four steps: (1) pose and position data are acquired from the robot dog’s own inertial sensors, (2) terrain and environment information is input from onboard cameras, (3) information is fused (integrated), and (4) path planning and motion control proposals are made. Ultimately, this work provides a robust framework for future developments in the vision-based navigation and control of quadruped robots, offering potential solutions for navigating complex and dynamic terrains. Full article

Background: Hydraulic quadruped robots have broad application prospects. Control system design is the core content of robot design. However, the micro-controllers used in the past have shortcomings such as long sampling period and simple algorithm. Methods: An electric control system of the layered, distributed structure for hydraulically actuated quadruped robots is designed considering a dog as a bionic model. In order to improve the response time and the steady precision of the system at the same time, a Fuzzy–PID compound control algorithm is put forward in this paper. The hardware and software of the control system are designed. Results: The lower computer’s control system for hydraulically actuated quadruped robots is developed using TMS320F28335 in series of DSP2000 as the core processor. Outside control circuit expands some external chips, such as AD7606, AD5754R, and PCA82C250, and a peripheral interface circuit is designed. Taking full advantage of the efficient processing power of the chip and the rich on-chip resources, the hardware circuit is simpler and reliable, and the software is also easy to implement. It is verified that the control system is rational and effective using experiments. Conclusions: The experimental results show that the control system designed in this paper is reasonable and can effectively control the joints of the quadruped robot. It has strong scalability and can meet the basic requirements of the autonomous mobile robot control system. Full article

Aiming at the nonlinear expansion/contraction drive problem between different cables in multi-joint cable drive mechanisms, a mechanical drive method based on a non-circular gear drive was proposed, which could replace the servo-sensing control system and minimize the system’s complexity and cost. A multi-joint single-degree-of-freedom (DOF) bending mechanism was constructed with several T-shaped components and cross-shaped components. The principle of the multi-joint mechanism driven by non-circular gears was clarified. The corresponding relationships between the joint bending angle, cables’ extension/retraction amount and non-circular gear transmission ratio were established. Using the Bowden cable driving, a multi-DOF bending mechanism decoupling scheme was proposed. Considering the adverse effect of non-circular gear hysteresis on the motion of multi-joint mechanisms, a non-circular gear backlash elimination method was proposed. The expression of the backlash of the non-circular gear with respect to the axial movement amount was deduced, which could enable the precise control of the backlash. A two-DOF multi-joint bionic mechanism driven by the non-circular gear was developed. The experimental results show that the mechanism can achieve coordinated bending motion by precisely controlling the line extension/contraction through non-circular gears. This multi-joint bionic mechanism driven by non-circular gears has the characteristics of reliable structure and simple control, and it is expected to be applied to bionic fish and bionic quadruped robots in the future. Full article

The inspiration for the footed robot was originally derived from biology, and it was an imitation of biological form and movement. In this paper, a bionic-robot dog is designed to reveal the motion characteristics of a quadruped robot mechanism through modeling, model kinematic analysis, and other methods. First, the structural characteristics and movement characteristics of the developed bionic-dog model are studied. The first step is to study the physiological structure of the dog, analyze the function of the dog’s limbs, and then use a high-speed camera to capture the motion of the marked bionic-robot dog and shoot motion video of the bionic-robot dog in different motion states. The effective data of the marked points in the video are extracted using PHOTRON 1.0 software, and the extracted data are analyzed and processed in the software MATLAB R2020a, and finally the structural characteristics and motion laws of the bionic-robot dog are obtained. Then, a bionic-robot-dog experimental platform is built to conduct experiments with three planned gaits (dynamic gait, static gait, and gait transition). The experiments showed that the three gaits were consistent with the planned movements and the bionic-robot dog could perform stable fast-gait walking, slow-gait walking, and quickly complete gait transitions. All three gaits were simulated in ADAMS 2019 software, and the simulation results showed that all three gaits caused the bionic dog robot to move smoothly. Full article

When a quadruped robot is climbing stairs, due to unexpected factors, such as the size of the differing from the international standard or the stairs being wet and slippery, it may suddenly fall down. Therefore, solving the self-recovery problem of the quadruped robot after falling is of great significance in practical engineering. This is inspired by the self-recovery of crustaceans when they fall; the swinging of their legs will produce a resonance effect of a specific body shape, and then the shell will swing under the action of external force, and self-recovery will be achieved by moving the center of gravity. Based on the bionic mechanism, the kinematics model of a one-leg swing and the self-recovery motion model of a falling quadruped robot are established in this paper. According to the established mathematical model, the algorithm training environment is constructed, and a control strategy based on the reinforcement learning algorithm is proposed as a controller to be applied to the fall self-recovery of quadruped robots. The simulation results show that the quadruped robot only takes 2.25 s to achieve self-recovery through DDPG on flat terrain. In addition, we compare the proposed algorithm with PID and LQR algorithms, and the simulation experiments verify the superiority of the proposed algorithm. Full article

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. Full article

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. Full article

To increase the knowledge and exploit new resources beyond the Earth, planetary surface exploration on the Moon or Mars attracts significant attention around the globe. Due to the fact that these planetary surfaces are widely covered by soil-like materials, various structures of planetary rovers have been proposed to adapt to the terrains. Nonetheless, the traditional rover structures, such as wheeled and leg-wheeled, have shown limitations in moving on granular soils. To improve the mobility, this paper proposes a multi-toe quadruped robot inspired by the desert chameleon animal. The key features are that each bionic foot possesses four toes to stabilize them on granular materials. Moreover, a bionic flexible spine is designed to coordinate with walking and turning gaits and to make the robot approach an animal-like mobility. To assess the robot performances, kinematics analysis and analytical modeling of foot, leg, and spine movements are carried out. The results demonstrate that this robot can effectively walk and turn in accordance with the adopted gaits. Finally, field tests of moving over sands have been conducted. It shows that the robot can stably walk and turn on sands, which indicates that it is adaptable to planetary granular terrains. Full article

In order to make a robot track a desired trajectory with high precision and steady gait, a novel intelligent controller was designed based on a new mechanical structure and optimized foot trajectory. Kinematics models in terms of the D-H method were established to analyze the relationship between the angle of the driving joint and the foot position. Inspired by a dog’s diagonal trot on a flat terrain, foot trajectory planning in the swing and support phases without impact were fulfilled based on the compound cycloid improved by the Bézier curve. Both the optimized cascade proportional–integral–derivative (PID) control system and improved fuzzy adaptive PID control system were applied to realize the stable operation of a quadruped robot, and their parameters were optimized by the sparrow search algorithm. The convergence speed and accuracy of the sparrow search algorithm were verified by comparing with the moth flame optimization algorithm and particle swarm optimization algorithm. Finally, a co-simulation with MATLAB and ADAMS was utilized to compare the effects of the two control systems. The results of both displacement and velocity exhibit that the movement of a quadruped bionic robot with fuzzy adaptive PID control systems optimized by the sparrow search algorithm possessed better accuracy and stability than cascade PID control systems. The motion process of the quadruped robot in the co-simulation process also demonstrates the effectiveness of the designed mechanical structure and control system. Full article

The leg structure with high dynamic stability can make the bionic biped robot have the inherent conditions to perform elastic and highly dynamic motion. Compared with the quadruped robot, the leg structure of the biped robot is more complex and has more degrees of freedom. This also complicates kinematic and dynamic modeling. In this paper, the kinematics model of a bionic biped robot is established. The leg configuration of the robot is a series parallel hybrid mechanism with five active joints and six passive joints. The mechanism is a spring mass model that interacts organically with the environment and mimics the characteristics of human walking well. By analyzing the topological configuration of leg mechanism, we use the screw theory to establish the forward and inverse kinematics models. Then, we build the prototype, and use a step gait to test the model and prototype. The research of this paper has obvious application significance for the design and iteration of biped robot prototype. Full article