Indoor navigation with a swarm of flying robots

Abstract

Abstract-Swarms of flying robots are promising in many applications due to rapid terrain coverage. However, there are numerous challenges in realising autonomous operation in unknown indoor environments. A new autonomous flight methodology is presented using relative positioning sensors in reference to nearby static robots. The entirely decentralised approach relies solely on local sensing without requiring absolute positioning, environment maps, powerful computation or longrange communication. The swarm deploys as a robotic network facilitating navigation and goal directed flight. Initial validation tests with quadrotors demonstrated autonomous flight within a confined indoor environment, indicating that they could traverse a large network of static robots across expansive environments.

On-board range-based relative localization for micro air vehicles in indoor leader–follower flight

“…To increase the versatility of the solution, MAVs should thus use on-board sensors to determine the locations of neighboring MAVs. Often, vision based methods are employed, such as: onboard camera based systems (Nägeli et al, 2014;Iyer et al, 2013;Conroy et al, 2014;Roelofsen et al, 2015), or infrared sensor systems (Kriegleder et al, 2015;Stirling et al, 2012;Roberts et al, 2012). A drawback of these systems is that they have a limited field of view.…”

A low cost omnidirectional relative localization sensor for swarm applications

“…There are several distinct ways to solve the localization problem, however considering the application of SR imposes some limitations. In [3] Stirling et al observed that "Global Information" (GI) cannot be used in such a localization system, which are environmental maps, centralized processing, absolute positioning and long-range communications. Furthermore, the ambient environment might impose other restrictions such as light conditions and obstacles [4] or temperature variations [5] depending on the system.…”

Self-swarming robots that exploit hydrodynamical interaction

“…In constructing swarm robotic systems, an important problem is how to make the agents interact with each other. In most of the previously developed swarm robotic systems, the agents interacted directly with each other by transmitting information such as their locations, identification numbers, and internal states [1][2][3][4][5][6][7][8][9][10][11][12][13][14] (Figure 1(a)). However, the previous swarm robots, which relied intensively on this informational interaction, still exhibited limited adaptability.…”