Robots have significant advantages over humans at performing tasks in extreme environments such as object collection in disaster sites. In such cases terrain of the disaster site is very uneven and can cost differently for different robots to travel over. Also in many cases, robots are required to move to multiple locations and perform multiple different tasks. In these cases robots performing the task to be composed of different types can be beneficial. Such as flying robots for traveling harsh surface with ease but incapable of carrying heavy object, ground robots for carrying heavy objects and robots with various equipment for various tasks can be used in each cases. To efficiently perform tasks in each cases task scheduling algorithms are needed. Scheduling algorithm should consider resources, such as energy and time, consumed to move to places for tasks and to perform the task. Since robots have limited capacity of energy, it needs to be considered as well.
We research on algorithms that can schedule heterogeneous multi robots to perform tasks in different conditions. Cases where all the robots and task locations are previously known, or unknown, where each robot is capable of achieving more than one tasks or each robot can only perform one task, where tasks are continuously generated while robots are active or all the tasks are present before scheduling is done.