To realize a wide range of functions in a complex environment, the transition is necessary between various motions suited to each environment. This article presents a transformable hexapod robot, RHex-T3, which is capable of switching to leg, wheel, and RHex mobile modes to improve its flexibility, and climbing the ladders with the hook-mode. The mechanical design and the implementation of the RHex-T3 are introduced, especially the coaxial transmission mechanism and the innovative 2-degree-of-freedom transformable leg. As the result, experiments are conducted to demonstrate the feasibility and successful performance of the proposed coaxial transformable mechanism. The locomotion performance under three basic mobile modes is evaluated through a series of indoor and outdoor experiments. Furthermore, the ladder climbing function is also verified and its boundary conditions are discussed.

[abstFig src='/00290003/02.jpg' width='300' text='Underactuated rimless wheel model for collisionless walking' ] In this paper, control methods for achieving collisionless walking of robotic underactuated walkers are discussed. Collisionless walking is a gait type of motion that does not cause collision during the landing of the swing-leg end. First, we introduce a simple point-footed walker and develop its motion equation. Second, we propose two time-scale output deadbeat control approaches and demonstrate mathematically their ability to generate a stable, collisionless walking gait. Overcoming potential barriers at midstance as well as the stability of zero dynamics are guaranteed accordingly. Furthermore, we investigate fundamental gait properties through numerical simulations.

Legged robots face inherent challenges in energy efficiency and stability at high speeds due to the repetitive acceleration–deceleration cycles of swing-based locomotion. To address these limitations, this paper presents a motion strategy that uses rolling gait instead of swing gait to improve the energy efficiency and stability. First, a wheel-legged quadruped robot, R-Taichi, is developed, which is capable of switching to legged, wheeled, and RHex mobile modes. Second, the mechanical structure of the transformable two-degree-of-freedom leg is introduced, and the kinematics is analyzed. Finally, experiments are conducted to generate wheeled, legged, and RHex motion in both swing and rolling gaits, and the energy efficiency is further compared. The experimental results show that the rolling motion can ensure stable ground contact and mitigate cyclic collisions, reducing specific resistance by up to 30% compared with conventional swing gaits, achieving a top speed of 0.7 m/s with enhanced stability (root mean square error (RMSE) reduction of 22% over RHex mode). Furthermore, R-Taichi exhibits robust multi-terrain adaptability, successfully traversing gravel, grass, and obstacles up to 150 mm in height.

Due to the development of wearable monitoring systems and the gradually expanding application demand, research interest has turned to free-form microstructures design capable of realizing superior and stable piezoresistive responses. The deep learning methods can accelerate and improve microstructure design with data-driven precision and increased efficiency. In this study, the concept of programmable microstructure is introduced to digitalize microstructure unit, convolutional neural network (CNN) model and Tabu-Search algorithm are respectively used to predict and search iteratively novel stress-voltage (S-V) responses from the finite element modeling (FEM) training set. Therefore, efficient exploration of parameter space and faster generating of novel microstructure designs can be achieved by the proposed algorithm framework, and the optimized microstructure has also been experimentally validated. Moreover, the working mechanism of the sensing medium layer is explicated by the resistance evolution of Ti₂CT_x-MXene atomic layers under the compressive strain via density functional theory calculations. The proposed AI-based tactile sensor exhibits high sensitivity, large linearity, fast response, and excellent cycling stability, it leverages strong capabilities to detect human being’s subtle activities and terrain perception of snake robot. This study could achieve a higher degree in human physiological monitoring and robot tactile construction, and gain a new insight for digital microstructure in sensor design.