Planetary exploration requires efficient methods for subsurface sampling, especially in extreme energy limitations. Traditional drilling methods are often energy intensive and require large platforms, limiting their applicability. Bio-inspired burrowing techniques, inspired by animals like moles, offer lightweight, low-power alternatives suitable for small robotic platforms. This paper presents a novel bio-inspired robotic platform, the Mole-like Incisor-Burrowing Robotic Platform (MIRP), designed to mimic the incisor-burrowing behavior of naked mole rats. The MIRP features an 11 DOFs mechanism with a compact design (220 mm × 140 mm × 80 mm) and uses servomotors to achieve low energy consumption. The robot combines a qu0adrupedal locomotion mechanism with an incisor-burrowing mechanism, allowing it to navigate granular terrains and perform excavation tasks. Kinematic analysis, including inverse kinematics and close-chain analysis, was conducted to optimize the robot’s motion strategy. A prototype was developed and tested in a simulated lunar regolith environment to test its maneuverability and burrowing performance. The power consumption of the prototype is below 10 W. This work validates the feasibility of bio-inspired incisor-burrowing for planetary exploration, offering a cost-effective and efficient solution for future extraterrestrial missions.

The mobile robots possess immense application potential in planetary exploration, field investigation and other related fields. Adopting suitable movement modes in multiplex task scenarios and flexible modes transformations significantly enhance the flexibility and mobility efficiency of robots. Therefore, a novel multi-modal mobile robot with various ground and aerial movement modes is proposed. Notably, different modes transformation and aerial manipulation can be smoothly performed during aerial maneuvers, thereby improving the deployment efficiency of robots. Firstly, the proposed multi-modal robot achieves high-integration and high-mobility efficiency in all modes through the iterative optimization design. Subsequently, a comprehensive hybrid dynamic model of the robot is established. Based on the dynamic model, the leg motion trajectory during the aerial transformation is planned by optimizing the coupling torque, minimizing the motion's interference on the flight system. Additionally, controllers for various movement modes are designed, including a novel flight controller based on the trajectory linearization control (TLC) method with an extended state observer (ESO), compensating for the time-varying inertial parameters of the robot and coupling or external disturbances, improving the agility and stability of the system in aerial. Finally, the practicability and effectiveness of robot’s multi-modal mobility, modes transformations and aerial manipulation are validated through simulations and real-world experiments.

Roller skating with passive wheels on a quadrupedal robot is more efficient than traditional walking. However, the typical mammalian quadruped robot with 3-DoFs legs can only perform one dynamic roller skating gait and has difficulty achieving turning motion. To address this limitation, we designed a novel quadrupedal robot with each leg having 4-DoFs to enable various roller skating locomotion including Swizzling, Stroking, and trot-like gaits while easily achieving turning motions. We considered the geometrical characteristics of the passive wheel and used the Levenberg-Marquardt method in robot kinematics to improve precision for both roller skating kinematics and contact point position for the dynamics controller. The position of the robot foot and the yaw angle of the passive wheel are decoupled for motion planning of all proposed gaits. Our proposed kinematics with wheeled geometry was verified through experiments to have higher precision, while the feasibility of all proposed roller-skating gaits was confirmed during straight motion and turning motion with a small radius on our prototype robot. Finally, we discussed the mobility efficiency of different roller skating gaits which were found to be more efficient than walking.

Legged mobile manipulators are receiving much more attention. Mobile platforms can infinitely expand the workspace of robotic arms, providing more possibilities for robot application scenarios. Compared with wheeled mobile manipulators, legged mobile manipulators have higher requirements for cooperative control of legged robots and robotic arms. This work decouples the control of the robotic arm and the legged robot. On the legged robot side, we explicitly estimate the wrench exerted by the robotic arm on the base and bring it into the legged robot’s dynamics, and then use a nonlinear model predictive controller (NMPC) to control the legged robot. On the robotics arm side, we adopt an impedance controller to realize the end-effector’s force control, and the introduction of impedance control has improved the safety and interactivity of legged mobile manipulators. We conducted experiments on physical robot to compare the differences between decoupled control and independent control, and the results show that the stability and robustness of robot systems have improved using decoupled control.

Visual SLAM methods based on point features have achieved acceptable results in texture-rich static scenes, but they often suffer from a deficiency of texture and the existence of dynamic objects in real indoor scenes, which limits the application of these methods. In this paper, we have presented DRG-SLAM, which combines line features and plane features into point features to improve the robustness of the system. We tested the proposed algorithm on publicly available datasets, and the results demonstrate that the algorithm has superior accuracy and robustness in indoor dynamic scenes compared with the state-of-the-art methods.