The purpose of this study is to investigate the dynamic characteristics of a roadheader for breaking rocks containing different numbers and sizes of predrill holes. A series of experiments was performed to quantitatively measure the cutting torque, thrust force, and specific energy during the cutting of a cutterhead. Experimental results show that the cutting torque, thrust force, and specific energy decrease as the number of predrill holes increases. When the number of predrill holes is nine, type 9‐2 exhibits the minimum cutting load and specific energy. In addition, three‐dimensional numerical simulations were conducted using LS‐DYNA software, and the results were further validated with experimental data. Numerical results reveal that the confining pressure has significantly affected the rock‐breaking process, and under the confining pressure of 10 MPa, values of the cutting torque and thrust force are 8.9% and 8.6% higher than those without confining pressure. The optimal diameter of the predrill holes is set as 12.5% of the maximum diameter of the cutterhead. Furthermore, the number of the holes is set as six, that is, one central hole and five circumferential holes, with a diameter of 45 mm according to the arrangement of type 6‐1.

As terrestrial resources become increasingly depleted, the demand for deep-sea resource exploration has intensified. However, the extreme conditions in the deep-sea environment pose significant challenges for underwater operations, necessitating the development of robust detection robots. In this paper, we propose an advanced path planning methodology that integrates an improved A* algorithm with the Dynamic Window Approach (DWA). By optimizing the search direction of the traditional A* algorithm and introducing an enhanced evaluation function, our improved A* algorithm accelerates path searching and reduces computational load. Additionally, the path-smoothing process has been refined to improve continuity and smoothness, minimizing sharp turns. This method also integrates global path planning with local dynamic obstacle avoidance via DWA, improving the real-time response of underwater robots in dynamic environments. Simulation results demonstrate that our proposed method surpasses the traditional A* algorithm in terms of path smoothness, obstacle avoidance, and real-time performance. The robustness of this approach in complex environments with both static and dynamic obstacles highlights its potential in autonomous underwater vehicle (AUV) navigation and obstacle avoidance.