Wheeled-legged humanoid robots combine the rough terrain compliance of humanoid robots with the high efficiency of wheeled robots, enabling the robot to achieve flexible and stable locomotion over multiple terrains. However, the stability control of the wheel-legged humanoid robot in dealing with rough terrains and unexpected external disturbances remains unsolved. In the current investigation, a compliant balance control framework (CBCF) is proposed, which can absorb ground shocks, withstand unexpected external disturbances, and remain stable posture during motion. The CBCF connects the control of legs movement and the wheels balance control through the movement of the robot's center of mass. The wheel balance control employs the inverted pendulum model and controls the two wheels through model prediction. The leg posture control utilizes a whole-body dynamic compensator to realize the compliant motion and remain a stable posture. Cooperating with the high-level motion planner, the CBCF can allow the BHR-WI to move quickly and perform excellent adaptation in unmodeled rough terrains, and it is able to appropriately handle unexpected external disturbances as well. It is also worth mentioning that the BHR-WI is capable of remaining balance and quickly recovering stability in the event of a disturbance, even if one of the legs leaves the ground. Finally, tests confirm that the BHR-WI could withstand sustained unexpected disturbances, could smoothly cross the grass and steps and even realize high maneuverability in jumping.

Biped robots with dynamic motion control have shown strong robustness in complex environments. However, many motion planning methods rely on models, which have difficulty dynamically modifying the walking cycle, height, and other gait parameters to cope with environmental changes. In this study, a heuristic model-free gait template planning method with dynamic motion control is proposed. The gait trajectory can be generated by inputting the desired speed, walking cycle, and support height without a model. Then, the stable walking of the biped robot can be realized by foothold adjustment and whole-body dynamics model control. The gait template can be changed in real time to achieve gait flexibility of the biped robot. Finally, the effectiveness of the method is verified by simulations and experiments of the biped robot BHR-B2. The research presented here helps improve the gait transition ability of biped robots in dynamic locomotion.

Biped robots swing their legs alternately to achieve highly dynamic walking, which is the basic ability required for them to perform tasks. However, swinging of the swinging leg in the air will disturb the interaction between the supporting leg and the ground and affect the upper body’s balance during dynamic walking. To allow the robot to use its own intrinsic motion characteristics to maintain stable movement like a human when its lower limbs are affected by unknown disturbances during dynamic walking, the ability to use its arms to resist disturbances is essential. This article presents a hybrid momentum compensation control method for torque-controlled biped robots to adapt to unknown disturbances during dynamic walking. First, a hybrid angular momentum and linear momentum regulator is designed to compensate for the disturbance caused by the swinging leg. Second, based on real-time dynamic state changes of the legs, a mixed-momentum quadratic programming controller is designed to realize stable dynamic walking. The proposed method allows the force-controlled robot to maintain its balance while walking down an unknown platform, and it maintains good straightness in the forward direction of dynamic motion. The proposed method’s effectiveness is verified experimentally on the BHR-B2 force-controlled biped robot platform.

Continuous bipedal jumping primarily involves consistently generating explosive movements and effectively managing landing impacts, which presents significant challenges. First, we propose a tracking controller based on sliding-mode regularized predictive control (SMRPC) to enable the robot stably return to its initial state along periodic trajectories and swiftly execute the next jump. For maintaining stable centroidal motions, the SMRPC generates a lumped wrench for the whole robot based on periodic trajectories. Then, the method distributes the lumped wrench to both foot surfaces by using regularized input. Second, we present a task-space compliance control to absorb impacts upon landing and manage transitions between ground and in-air phases. This task-level controller utilizes foot wrench feedback to incorporate vertical velocity compensation, thereby achieving whole-body compliance. Finally, the effectiveness of our control framework is demonstrated on a humanoid robot named BHR-B2, which successfully performs stable continuous jumps in both simulated and experimental environments.

In this paper, a novel disturbance rejection approach is developed for a class of nonlinear systems, which incorporates the Kalman filter into the equivalent-input-disturbance (EID) structure. First, the EID-based control system and the configuration of the Kalman Filter are illustrated. Then, an optimal estimation theorem is obtained by analyzing the dynamic of the Kalman filter, and a special Kalman gain is derived. Next, the dynamics of the closed-loop system are deduced, and stability is guaranteed based on the Lyapunov function. Finally, simulations with comparison are carried out to demonstrate the excellent performance of both disturbance rejection and noise attenuation.