Coordinating teams of aerial robots in cluttered three-dimensional (3D) environments requires a principled integration of discrete mission planning-deciding which robot serves which goals and in what order -- with continuous-time trajectory synthesis that enforces collision avoidance and dynamic feasibility. This paper introduces IMD-TAPP (Integrated Multi-Drone Task Allocation and Path Planning), an end-to-end framework that jointly addresses multi-goal allocation, tour sequencing, and safe trajectory generation for quadrotor teams operating in obstacle-rich spaces. IMD--TAPP first discretizes the workspace into a 3D navigation graph and computes obstacle-aware robot-to-goal and goal-to-goal travel costs via graph-search-based pathfinding. These costs are then embedded within an Injected Particle Swarm Optimization (IPSO) scheme, guided by multiple linear assignment, to efficiently explore coupled assignment/ordering alternatives and to minimize mission makespan. Finally, the resulting waypoint tours are transformed into time-parameterized minimum-snap trajectories through a generation-and-optimization routine equipped with iterative validation of obstacle clearance and inter-robot separation, triggering re-planning when safety margins are violated. Extensive MATLAB simulations across cluttered 3D scenarios demonstrate that IMD--TAPP consistently produces dynamically feasible, collision-free trajectories while achieving competitive completion times. In a representative case study with two drones serving multiple goals, the proposed approach attains a minimum mission time of 136~s while maintaining the required safety constraints throughout execution.

翻译：在杂乱的三维环境中协调无人机编队需要将离散任务规划（决定哪个机器人服务于哪个目标及其顺序）与确保避碰和动态可行性的连续时间轨迹生成进行原理性集成。本文提出IMD-TAPP（集成多无人机任务分配与路径规划）——一种端到端框架，可联合解决四旋翼编队在障碍密集空间中的多目标分配、路径排序与安全轨迹生成问题。IMD-TAPP首先将工作空间离散化为三维导航图，通过基于图搜索的路径规划计算考虑障碍的机器人-目标与目标-目标运动成本。这些成本随后嵌入由多线性分配引导的注入式粒子群优化方案中，以高效探索耦合的分配/排序替代方案，最小化任务完成时间。最后，通过配备迭代障碍间隙与机间距离验证的生成-优化例程，将得到的航点路径转化为时间参数化的最小加加速度轨迹，并在安全裕度被违反时触发重新规划。在杂乱三维场景下的大量MATLAB仿真表明，IMD-TAPP始终能生成动态可行且无碰撞的轨迹，同时实现具有竞争力的完成时间。在包含两架无人机服务多个目标的代表性案例研究中，该方案在全程保持所需安全约束的前提下实现了最小136秒的任务时间。