Mobile Robots Charging Assignment Problem with Time Windows in Robotic Mobile Fulfilment System A customerdriven Ecommerce economy leads to a higher expectation on delivery of products. The lead time in the supply chain becomes shorter and shorter and a higher efficiency on picking and packing activities for the warehouse is required. Compared with the traditional warehouse, robotic mobile fulfilment system can increase the efficiency of picking products to fulfil the orders with the characteristics of high volume and high variety consumption pattern. A mobile robot with a mobile storage rack follows the positioning identifier for moving. In the context of Ecommerce implementation, datadriven optimization is one of the objectives for the robotic mobile fulfilment system. Data are collected from different sources such as sensor, tracking data and demand traffic. The objective of this paper is to simulate the charging activities for mobile robot under different designed instances. The results of the model show the charging time of different battery capacity of RC time and charged percentage.

An Efficient Recharging Task Planning Method For MultiRobot Autonomous Recharging Problem As robots are increasingly employed in the warehouse operation, an important problem that needs to be solved is the Autonomous Recharging Problem (ARP); that is deciding when and where to recharge robots. Former research in ARP is disjoint that only focuses on one of above two questions, considering the high computation time. In this paper, we describe an efficient recharging task planning method to solve ARP and it includes two phases: In the first phase, recharging task planning based on task sequence segmentation is proposed for individual robot, in which both when to recharge and where to recharge are considered to maximize operational efficiency. And it also improves the computation efficiency by segmenting task sequence and planning each recharging task recursively. In the second phase, all robots task sequences with planned recharging tasks are centralized and selected recharging stations of some planned recharging tasks are reallocated, using maximum bipartite graph matching to reduce waiting time for other robots recharging and improve overall task execution efficiency. The proposed method is validated by means of simulation in a real warehouse environment.