In this paper we present a study of a robotic system that consists of an unmanned aerial vehicle equipped with a pair of manipulator arms (MMUAV), and unmanned ground vehicles (UGVs). The envisioned application scenario includes autonomous packet transportation, where MMUAV is used for picking/placing packets, while both MMUAV and UGV can be used for packet transportation, with different energy consumption profiles. We propose a reactive method for decentralized task planning and coordination of robots using hierarchical task decomposition based on TÆMS framework. Our approach takes into account low-level motion-planning aspects of the system as well as high-level mission specification, making this a multi-layered system. For low-level planning we use sampling-based planner combined with obstacle-free trajectory generation. Methods are verified in simulations and on an experimental testbed, using 3D Robotics quadcopter and Pioneer 3DX mobile robots with the results showing stability and robustness of the presented methods.

This paper presents the results of our efforts to build a heterogeneous robotic system capable of executing complex disaster response and recovery tasks. We aim to explore high level task scheduling and mission planning algorithms that enable various types of robots to cooperate together, utilizing each others strengths to yield a symbiotic robotic system. In the proposed scenario, a ground vehicle and an aerial robot work together to close a valve in a disaster stricken industrial environment. To that end we use TAEMS framework in order to specify interrelationships between mission subtasks and develop an effective scheduling and coordination mechanism, inspired by Generalized Partial Global Planning. We present simulation results with two different outcomes that show cooperative capabilities of the system.

In this article we present a mathematical model of a spincopter - an inherently stable and easy to control unmanned aerial vehicle (UAV). Although the devised model represents only the first approximation of spincopter's physics, it captures basic phenomena that are sufficient for derivation and testing of a simple control algorithm. Results obtained by simulations in Simulink®, presented herein, demonstrate efficient performance of the proposed simple controller structure. Further tests, including investigation of complex aerodynamics effects and hardware-specified limitations, have been done using X-Plane®software package. Finally, the proposed controller has been tested experimentally. Both, X-Plane®and experimental results confirmed the outcome from Simulink®.