A multirobot simulator for the evaluation of formation control algorithms Autonomousunmanned driving has the capability to provide numerous benefits such as better traffic management, increased safety, reduced emission, and enhanced transportation network. Once autonomous ground vehicles (AGVs) are deployed, they will have to interact with other such vehicles. Interaction between multiple AGVs is an important area of research where analysis on the performance of algorithmscontrol schemes of AGVs is carried out. Performing realworld experiments with teams of autonomous vehicles is a challenging task due to cost and complexity. On the other hand, a simulation can emulate reality and provide an inexpensive and less timeconsuming development process compared to the real world robotsxe2x80x99 testing. Therefore, a simulation tool is developed for multirobot navigation. This simulator is based on opensource Robot Operating Systems (ROS) and natively supported robotics simulator Gazebo.

Multi Robot Route Planning (MRRP): Extended SpatialTemporal Prioritized Planning Autonomous vehicles are, in contrast to classical automated guided vehicles (AGVs), less predictable in their behavior and drive time. Therefore, the issue of how to efficiently control these vehicles arises, because autonomous agents need to be coordinated and not controlled, to give autonomous behaviors and actions space. The scientific contribution of this paper is a novel approach, based on prioritized planning to target this issue as well as an open source framework for evaluation and comparison. Prioritized planning has the disadvantage of being neither optimal nor complete, however, it has the advantage of being computationally feasible. This work utilizes prioritized planning to significantly increase the set of feasible scenarios through collision prevention: by locally finding alternative routes and adding them to the search graph. The paper clearly formulates the extensions needed and delineates the approachxe2x80x99s limits, as it is neither optimal nor complete. More importantly, however, our method calculates routes for each vehicle with intervehicle synchronization, enabling vehicles to execute the plan in a distributed fashion without centralized control, thereby allowing autonomous behavior. Finally, results are verified by comparing our Multi Robot Router (MRR) proposed in this work to classical approaches. The software developed as well as the test sets are publicly available for ROS and the simulation environment.