In this paper, we study a cooperative aerial-ground robotic team and its application to the task of automated construction. We propose a solution for planning and coordinating the mission of constructing a wall with a predefined structure for a heterogeneous system consisting of one mobile robot and up to three unmanned aerial vehicles. The wall consists of bricks of various weights and sizes, some of which need to be transported using multiple robots simultaneously. To that end, we use hierarchical task representation to specify interrelationships between mission subtasks and employ effective scheduling and coordination mechanism, inspired by Generalized Partial Global Planning. We evaluate the performance of the method under different optimization criteria and validate the solution in the realistic Gazebo simulation environment.
This paper describes an underwater acoustic sensor network consisting of a heterogeneous robotic swarm used for long-term monitoring of underwater environments. The swarm consists of a large number of underwater robots acting as sensor nodes with limited movement capabilities, and a few surface robots aiding them in accomplishing underwater monitoring scenarios. Main interactions between two types of robots include underwater sensor deployment and relocation, energy and data exchange, and acoustic localisation aiding. Hardware capabilities of each vehicle are described in detail. Inter-agent communication is split into two layers: surface and underwater communication. Surface communication utilises wireless communication using WiFi routers configured for decentralised routing. Underwater communication mainly uses acoustic communication which, when used within a large swarm, poses a challenging task because of high probability of interference and data loss. The acoustic communication protocol used to prevent these issues is presented in detail. Finally, more complex functionalities of the robotic swarm are presented, including several results from real-life experiments.
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 TAEMS 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.
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