Intelligent workshop UAV inspection path planning is a typical indoor UAV path planning technology. The UAV can conduct intelligent inspection on each work area of the workshop to solve or provide timely feedback on problems in the work area. The sparrow search algorithm (SSA), as a novel swarm intelligence optimization algorithm, has been proven to have good optimization performance. However, the reduction in the SSA’s search capability in the middle or late stage of iterations reduces population diversity, leading to shortcomings of the algorithm, including low convergence speed, low solution accuracy and an increased risk of falling into local optima. To overcome these difficulties, an improved sparrow search algorithm (namely the chaotic mapping–firefly sparrow search algorithm (CFSSA)) is proposed by integrating chaotic cube mapping initialization, firefly algorithm disturbance search and tent chaos mapping perturbation search. First, chaotic cube mapping was used to initialize the population to improve the distribution quality and diversity of the population. Then, after the sparrow search, the firefly algorithm disturbance and tent chaos mapping perturbation were employed to update the positions of all individuals in the population to enable a full search of the algorithm in the solution space. This technique can effectively avoid falling into local optima and improve the convergence speed and solution accuracy. The simulation results showed that, compared with the traditional intelligent bionic algorithms, the optimized algorithm provided a greatly improved convergence capability. The feasibility of the proposed algorithm was validated with a final simulation test. Compared with other SSA optimization algorithms, the results show that the CFSSA has the best efficiency. In an inspection path planning problem, the CFSSA has its advantages and applicability and is an applicable algorithm compared to SSA optimization algorithms.

To investigate the machining effect of ultrasonic honing microjets on a titanium–tantalum alloy surface, a cavitation microjet flow impingement model was established using the smoothed particle hydrodynamics–finite element method (SPH–FEM) coupling method including the effects of wall elastic–plastic deformation, the ultrasonic field and the honing pressure field. Simulation analysis was conducted on a single impact with different initial speeds and a continuous impact at a constant initial speed. The results showed that the initial speed of the microjet needed to reach at least 580 to 610 m/s in order to obtain an obvious effect of the single impact. The single impact had almost no effect at low speeds. However, when the microjet continuously impacted the same position, obvious pits were produced via a cumulative effect. These pits were similar to that obtained by the single impact, and they had the maximum depth at the edge rather than the center. With the increase in the microjet’s initial speed, the total number of shocks required to reach the same depth gradually decreases. When the number of impacts is large, with the increase in the number of impacts, the growth rate of the maximum pit depth gradually slows down, and even shows no growth or negative growth at some times. Using the continuous impacts of the microjet by prolonging the processing time can enhance titanium–tantalum alloy machining with ultrasonic honing for material removal.