Abstract:Abstract-A leader-follower formation driving algorithm developed for control of heterogeneous groups of unmanned micro aerial and ground vehicles stabilized under a top-view relative localization is presented in this paper. The core of the proposed method lies in a novel avoidance function, in which the entire 3D formation is represented by a convex hull projected along a desired path to be followed by the group. Such a representation of the formation provides non-collision trajectories of the robots and respe… Show more
“…This paper extends our previous work [34], where the basic formation driving mechanism based on the visual relative localization was introduced. The main extension consists in the fault diagnosis and recovery mechanism that is introduced in Fig.…”
“…This paper extends our previous work [34], where the basic formation driving mechanism based on the visual relative localization was introduced. The main extension consists in the fault diagnosis and recovery mechanism that is introduced in Fig.…”
“…Rotorcraft such as helicopters [ 21,22 ] and quadcopters [ 23–25 ] have been improving for many years. The working principles of quadcopters in particular have been extensively described in literature, [ 26–33 ] with most attention related to balance control and stability.…”
Sunlight energy is potentially excellent for small drones, which can often operate during daylight hours and fly high enough to avoid cloud blockade. However, the best solar cells provide limited power, compared to conventional power sources, making their use for aerial vehicles difficult to realize, especially in rotorcraft where significant lift ordinarily generated by a wing is already sacrificed for the ability to hover. In recent years, advances in materials (use of carbon-fiber components, improvement in specific solar cells and motors) have finally brought solar rotorcraft within reach. Here, the application is explored through a concise mathematical model of solar rotorcraft based on the limits of solar power generation and motor power consumption. Multiple solar quadcopters based on this model with majority solar power are described. One of them has achieved an outdoor airtime over 3 hours, 48 times longer than it can last on just battery alone with the solar cells carried as dead weight and representing a significant prolongation of drone operation. Solar-power fluctuations during long flight and their interaction with power requirements are experimentally characterized. The general conclusion is that solar cells have reached high enough efficiencies and can outperform batteries under the right conditions for quadcopters.
“…The abovementioned internal camera module can also be used to identify the exact location of other components of a configuration. Its strategy in [9] doesn't somehow allow for group driving to be reverted if an impediment in the vicinity requires it. To use the strategy in [7], the members following the ultimately enabled proceed in the path of continuous travel until the online leadership rotates clockwise, that might culminate in a clash with robotics at varied ranges from the virtually president's location, as illustrated in Fig.…”
Section: Strategy and Methods Of Implementationmentioning
This study will discuss the matter of movement communication and preparation of tight configurations of land & flying robots. Remotely Operated Cars (UGVs) and Unmanned Aerial Vehicles (UAVs), in specific Micro Aerial Vehicles (MAVs), would be used to fix circumstances where a creation of UGVs and UAVs, in specific Micro Aerial Vehicles (MAVs), should counteract their velocity and direction to finish a mission of traffic sequence to a targeted area. The motion planning and stabilisation strategy given here is a useful tool for deploying closely collaborating robot teams including both outdoor and indoor settings. The installation of large groups of Micro Aerial Vehicles (MAVs) in a legitimate (indoor and outdoor) environment without the use of auxiliary positioning applications (such as Vicon or GPS) is indeed a natural development in the area of autonomously flying systems. Stability, control, and trajectory planning techniques for guiding swarm or configurations of unmanned MAVs, as well as diverse groups with Unmanned Ground Vehicles (UGVs) operating alongside MAVs, will be discussed in greater detail. These approaches discussed all are designed for the use of inter squads in true complex scenarios even without necessity for worldwide translation or motion capture systems, as they are predicated on board optical comparative localisation of single MAVs. This multi - objective optimisation being an enabler for the introduction of swarming of tiny autonomous drones beyond the labs with equipment for precise robot positioning. Model Predictive Control (MPC) is being used to address a formations to goal territory issue, and the form drive idea is based on a simulated approach. The Particle swarm optimization approach is utilised for digital leader trajectories planning, as well as control and stabilisation of follows (MAVs and UGVs). The proposed technique could be tested in the future using a range of simulation and practical tests.
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