Bionic propulsion has advantages over traditional blade propellers, such as efficiency and noise control. Existing research on ray-inspired robot fish has mainly focused on a single type of pectoral fin as bionic propeller, which only performed well in terms of pure speed or maneuverability. Rarely has the performance of different fin types been compared on the same platform to find an optimal solution. In this paper, a modularized robot fish with high-fidelity biomimetic pectoral fins and novel multi-DOF propelling mechanism is presented. A kinematic model of the pectoral fin based on motion analysis of a cownose ray is introduced as guidance for the propelling mechanism design. A high-fidelity parametric geo-model is established and evaluated based on statistical data. The design and fabrication process of the 3D soft bionic fins, as well as the robot platform, is also elaborated. Through experiments comparing the performance of different fin types constructed with different materials and approaches, it was found that the new soft fins made of silicon rubber have better performance than traditional fins constructed with a flexible inner skeleton and a permeable outer skin as a result of better 3D profile preservation and hydrodynamic force interaction. The robot ray prototype also acquires a better combination of high speed and maneuverability compared to results of previous research.

Bionic propulsion has certain advantages over traditional propellers. Much research on pectoral fins as bionic propellers for ray-inspired robots has been made, but rarely did they compare the hydrodynamic performance of different fins on the same platform to find out optimal balance. In this paper, the existing prototypes are categorized into three structure types, and a new bionic pectoral fin module used on a ray-inspired robotic fish was presented, together with a novel 2-DOF spatial parallel mechanism as the bionic propeller. Motion analysis of the mechanism agreed well with the pectoral fin kinematic model, providing a reliable basis to test different types of fins. Design and fabrication of the new bionic fin module as well as two traditional ones are also explained. Hydrodynamic experiment was conducted to study the differences between each fin type under various working conditions. Results indicate that the thrust generated by the fin oscillation is closely related to four parameters (amplitude, frequency, phase difference, and flow velocity), and there are optimal value ranges for better propelling performance when the frequency is around 0.5 Hz and phase difference is near 30°. Thanks to better profile preservation and hydro force interaction, the newly proposed pectoral fins had higher performance than the traditional ones in terms of thrust generation and controllability when the amplitude is higher than 30° and frequency is over 0.3 Hz. An average thrust of 2.98 N was recorded for the new fin module at the max amplitude of 60°, 11.6% and 16.4% higher than the other two comparative test groups, respectively.

This letter presents a robust multi-sensor fusion framework for state estimation in legged robots (LLIO) based on an iterated extended Kalman filter. To address the limitations of IMU priori estimation, which often leads to legged robot localization errors or failures, our method integrates the contact constraints of the robot's leg kinematics with the ground. By introducing a sliding window-based ground contact constraint module, we effectively combine the contact state of the legged robot's foot with ground features, enhancing the constraints in complex environments and reduce localization drift. Additionally, factor graph optimization minimizes global cumulative drift. The proposed method has been extensively evaluated through numerous experiments and relevant public datasets. The results demonstrate that our approach significantly reduces local drift and better computational efficiency.