## 2 Related Works  
[PERSON], [PERSON] and [PERSON] et al. [11; 12] found that the task assignment problem under the above background is essentially the traveling salesman problem (TSP), which is almost the beginning of path planning-related problems. The vehicle routing problem (VRP) is the core of the current logistics practice, and it is derived from TSP and its variants such as probabilistic TSP and fuzzy TSP. With the development of VRP research, some complex variants have also been derived. For example, [PERSON] et al. [13] explored this cooperation by developing a model for the vehicle routing problem with drones that considers the presence of customer time windows (VRPTW). The concept of time windows is introduced into VRP by [PERSON], who proposed a branch and bound algorithm for small-scale problems [14]. [PERSON] [15] designed an improved simulated annealing algorithm with a crossover operator for the capacitated vehicle routing problem (CVRP). Combining multi-depot and integrated delivery to expand the VRPTW makes the MDVRPTW more scientific and reasonable, and the complexity of the solution is increased accordingly. [PERSON] and [PERSON] et al. [16; 17] presented an improved genetic algorithm for solving the MILP considering specific practical issues and related factors. Now we turn our attention to the SR literature. A recognized definition of SR was proposed by [PERSON] in 2005 [18]. [PERSON] [19] developed the first cellular robot system, which is a distributed system composed of many autonomous robots. [PERSON] and [PERSON] [20] discussed and analyzed the urgent need for standardization in many aspects of SR, including hardware and software, so that SR can be applied in real-world APPL. [PERSON] et al. [21] summarized the advantages of robot systems and carried out investigations on the search and tracking algorithms of SR. [PERSON] and [PERSON] [22] proposed an intelligent logistics scheduling system based on the Internet of Things, which realizes dynamic coordination between customers, sorting robots, and cloud technology, and then used an ant colony algorithm to avoid obstacles in scheduling. [PERSON] and [PERSON] [23; 24] mainly carried out the integrated system research of SR system generation, execution, and monitoring, providing an advanced multi-task planning solution. [PERSON] et.al. [25] proposed a task-oriented, auction-based task allocation framework, which is implemented in a multi-robot system, allowing tasks to be dynamically allocated to robots when a given task is completed. These literatures adopt different methods for the research goals to obtain the task allocation table and then update the execution according to the system framework. [PERSON] et.al. [26] developed a scheduling program for determining truck routes and robot launch locations based on the last mile problem, and then determined that the number of weighted delayed customer deliveries was minimized. [PERSON] et al. [27] studied the vehicle path problem of an unmanned aerial vehicle, sidewalk robot, or walking machine movement synchronization. From the above, robots have high-efficiency communication capabilities, adaptability to different tasks, and low-cost characteristics. These features provide huge opportunities for their application and development in intelligent logistics. Robotics is an important part of intelligent logistics and future logistics. Through the review and analysis of the existing literature, it is found that many documents mainly study the control system and hardware structure of robots, but the effective use of robots is also an important concept to strengthen the development of robotics in addition to the development of service components. So far, the research on the potential of supporting robot delivery is still insufficient, and these documents on robot VRP in logistics delivery did not consider the battery capacity limitations of the robot, the limited load capacity, and the impact of the load on the transportation capacity.