## 1 Introduction  
Initially, drones were valued by the military industries of various countries because of their stealth, relatively low cost, ease of operation, and lack of fear of casualties. Nowadays, the use of drones is gradually spreading from military [1] to education, film and television [2], agriculture [3], and service industries [4]. Drones are also known as flying robots or unmanned aerial vehicles [5]. Most of these vehicles are used for observation, search, and discreet planning [6]. Recent advances in UAV technology have made it possible to perform near-ground search and rescue (SAR) in complex environments such as urban and mountainous areas [7]. For example, during a rescue mission in Oregon, drones were used to identify fatalities in the Narrows Canyon and eliminate the need for search-and-rescue personnel to perform dangerous rope drops at night [8]. This technology can greatly reduce the search time, improve the efficiency of the rescue, and provide guidance assistance to teams in areas where manual patrols are difficult and time-consuming [9]. For now, drones still have very limited airspace activity in some areas, as shown in Figure 1. Missions in the no-fly zone require even more authorization and permission from the relevant authorities [10]. However, this would highly limit the scope of drone search and rescue and would not bring out the strengths and working standards of drones. Rational establishment and planning of the framework of drone-based search-and-rescue systems and the proper use of drones in urban and mountainous areas for near-ground search missions will provide great help to rescue [11].  
Unlike other commercial aircraft, the short takeoff and landing of drones in the vertical direction increases the suitability of drones for near-ground search among complex environments [12]. Nonetheless, drones still face significant challenges in performing search-and-rescue missions in the near field. At present, drone-based near-ground search and rescue usually has a similar set of constraints. First, the search time is tight and drones need to arrive at the mission site as quickly as possible, and any delay could lead to irreversible and serious consequences [13]. Secondly, the working environment is not friendly, and the drone has more complex scenes such as buildings and forests during low-altitude operations, which leads to an excessive number of total turning angles in the path generated by the drone. It is not only energy-consuming, but also increases the search time [14]. Third, due the dynamic threats that arise during the execution of the mission, the drones need to maintain a safe distance between the working environment and other dynamic obstacles [15; 16] to prevent the phenomenon of course conflict. These unfavorable constraints make it difficult for drones to complete missions in urban as well as mountainous low-altitude airspace.  
In order to solve the above-mentioned problems, this paper reduces the total length of the drone's generated path and the total turning angle of the path by introducing an any-angle path-planning strategy [17] and a path-smoothing technique [18] to reduce the time required and energy consumption for flight. Secondly, for dynamic threats in the mission environment, stable dynamic-obstacle avoidance techniques need to be introduced [19]. This is to avoid collision phenomena caused by possible obstacle changes and other drones' flight path conflicts in the complex operating environment.