We investigate the effect of adding cutaneous cues to kinesthetic feedback on the perception of a virtual object's hardness. A cutaneous haptic interface is designed to deliver hardness information to a user's fingertip along with a force-feedback interface, and the corresponding rendering strategy is implemented. Two sets of experiments are conducted to evaluate the proposed approach for hardness perception using one-finger touch and two-finger grasp. Experimental results indicate that the addition of cutaneous feedback can make the virtual surface feel significantly harder than the nominal stiffness delivered by force-feedback alone. In addition, the perceived hardness is significantly affected by the rate of hardness rendered with a cutaneous interface for the nominal stiffnessand 0.5 N/mm. For two-finger grip, the effect of a virtual object's thickness has a significant effect on the perceived hardness measured in stiffness. When the perceived hardness is converted to Young's modulus, the effect of thickness is insignificant.

We have proposed a flexible sensor that can sense shear and normal forces, and can be fabricated through a simple process using only one layer of polyvinylidene fluoride (PVDF) film. For the measurement of shear and normal forces, one layer of PVDF film was sealed in a three-dimensionally structured polydimethylsiloxane (PDMS). In the structure, the sensor produced voltage signals corresponding to the shear and normal forces. Using this property, we aimed to demonstrate how to sense the magnitude and direction of the force applied to the sensor from its output voltages. Furthermore, the proposed sensor with a 2 × 2 array was able to measure the applied force in real time.

Wheeled-legged humanoid robots combine the efficiency of wheels with the versatility of legs, offering significant advantages for locomotion. This paper proposes a hierarchical control framework for such robots, using a two-wheeled inverted pendulum with a roll joint (TWIP-R) as a template model. The framework integrates a motion planner and a whole-body controller. The motion planner utilizes a linear quadratic regulator (LQR) to dynamically adjust the zero moment point (ZMP), counteracting centrifugal forces and enabling stable, dynamic movements. Meanwhile, the whole-body controller (WBC), based on centroidal momentum, solves an optimization problem via quadratic programming (QP) while incorporating constraints from the rolling contact condition of the wheels and the dynamics of the humanoid robot. This framework generates optimized torque commands, enabling feasible and stable motion even in dynamic scenarios. Simulations featuring challenging maneuvers, such as slalom, demonstrate its ability to enhance stability and dynamic performance compared to traditional two-wheeled inverted pendulum (TWIP)-based methods by leveraging a dynamics model with roll motion. This framework highlights the potential of wheeled-legged humanoid robots to achieve dynamic, stable, and efficient locomotion in a variety of scenarios.

An analytic method to generate the real-time trajectory of the center of mass (CoM) is proposed for given zero moment point (ZMP) pattern. The whole walking process is divided into transient and periodic walking phases. For each phase of walking, we compute the analytic solution of the center of mass for given ZMP based on the inverted pendulum model. Specially, for the transient walking phase, we actively utilize the non-minimum phase solution to extract the center of mass trajectory. The proposed pattern generation method were implemented to a real humanoid robot system called by MAHRUII. Those are verified by the experiments.