Achieving stable and natural locomotion in bipedal robots, comparable to that of humans and animals, remains a long-standing challenge in robotics. In this work, we propose a bio-inspired low-level control framework that streamlines the generation of naturalistic gait patterns while ensuring adaptability. Our approach begins with the design of a low-dimensional gait representation that captures key characteristics of human and animal locomotion. This representation is then integrated with the Linear Inverted Pendulum Model (LIPM) to form an abstract yet effective motion descriptor. Serving as a kinematic reference within a reinforcement learning (RL) framework, this descriptor enables the training of control policies that strike a balance between biomechanical realism and adaptability. Rather than strictly adhering to predefined gait trajectories, the learned policies dynamically adjust to optimize both stability and velocity tracking. As a result, our method enables bipedal robots to exhibit smooth, biomechanically realistic locomotion while enhancing stability and adaptability. We validate the proposed framework through real-world experiments on our bipedal robot, demonstrating its ability to achieve stable and efficient locomotion.

For quadrupeds, a flexible spine allows them to traverse space and make quick turns. From the perspective of mechanical design in quadruped robots, an active spine with 2 degrees of freedom (2-DOF) can achieve dynamic posture adjustment similar to biological organisms which allows for pitch and yaw control. In this work, we present a novel approach to enhance the flexibility of a quadruped robot, Yatsen Lion II, by incorporating a 2-DOF active spine, which is mechanically designed as a linkage-driven parallelogram mechanism. To optimize its motion, we utilize nonlinear model predictive control (NMPC), which combines centroidal dynamics with full kinematics. By incorporating the two extra DOFs of the spinal joint into the generalized coordinates and velocities, we represent the robot as a hybrid dynamic system, capturing the intricate interplay between the legs and spine. Centroidal dynamics act as a crucial bridge between joint movements and the robot’s overall momentum, enabling the controller to synchronize the quadruped’s movements with dynamic spinal adjustments and adaptive gait patterns. We validate our approach through both simulation and real-world experiments. We compare spinal quadruped robot to their rigid-spine counterparts across key locomotion metrics, including in-place turning, straight-line speed, and turning radius. The results indicate that the spined quadrupedal robot outperforms its rigid counterpart by up to 26%, highlighting its flexibility.

Continuum robots, inspired by biological structures such as spines and tails, have attracted significant attention due to their flexibility and ability to perform complex tasks in confined and dynamic environments. However, traditional flexible continuum robots often encounter challenges such as non-linearity, hysteresis, and limited load-bearing capacity, which can compromise their precision and effectiveness in practical applications. To address these limitations, this paper presents a novel bionic continuum mechanism: Rigid Multi-joint Coupled Continuum Structure(RMCC), which employs a rigid mechanical transmission mode to couple all joints, achieving coordinated movement of multiple joints. Its rigid structural composition and transmission method provide it with high precision and load capacity. The coordinated motion of the joints endows it with the dexterity of a continuum mechanism, while also enabling efficient and precise control with a minimal number of motors. The modular joint design improves the system’s scalability and adaptability, enabling a wide range of configurations to suit diverse robotic applications. The feasibility and effectiveness of the proposed system are validated through a series of bio-inspired experiments, including lizardlike crawling, falling-cat movement, and adaptive grasping like birds. The experimental results confirm that the RMCC exhibits the flexibility and adaptability of animals, demonstrating its potential for diverse bionic robotics applications.

Quadrotors may crash and cause severe accidents under instantaneously drastic disturbances. To mitigate the effect of such disturbances, these critical issues should be considered: efficient disturbance observation and compensation, full attitude controllability, and instant output power generation of the quadrotor. In this paper, to keep the quadrotor stable even under suddenly drastic disturbances, a novel control framework is presented to by integrating the advantages of active disturbance rejection control (ADRC) as well as geometric control for a quadrotor with bidirectional thrust capabilities. Moreover, to strengthen the adaptability under significant disturbances, a novel switching strategy is introduced into the control framework by virtue of the quadrotor’s bidirectional thrust capabilities. The ADRC scheme is performed when the disturbances are within a range; alternatively, if the disturbances surpass the preset range and the desired control is beyond the ultimate output of the quadrotor, the quadrotor compliantly responds by executing a 180° flip reverse flight to handle such drastic disturbances. Numerical and real-world experiments demonstrate that the proposed robust control strategy has superior performance adapts to instantaneously drastic disturbances.