This paper presents a novel strategy for the autonomous deployment of Micro Aerial Vehicle scouts through constricted aperture-like ingress points, by narrowly fitting and launching them with a high-precision Mobile Manipulation robot. A significant problem during exploration and reconnaissance into highly unstructured environments, such as indoor collapsed ones, is the encountering of impassable areas due to their constricted and rigid nature. We propose that a heterogeneous robotic system-of-systems armed with manipulation capabilities while also ferrying a fleet of micro-sized aerial agents, can deploy the latter through constricted apertures that marginally fit them in size, thus allowing them to act as scouts and resume the reconnaissance mission. This work's contribution is twofold: first, it proposes active-vision based aperture detection to locate candidate ingress points and a hierarchical search-based aperture profile analysis to position a MAV's body through them, and secondly it presents and experimentally demonstrates the novelty of a system-of-systems approach which leverages mobile manipulation to deploy other robots which are otherwise incapable of entering through extremely narrow openings.
Launching a Micro–Scout UAV from a Mobile Robotic Manipulator Arm
This paper addresses the problem of autonomously deploying an unmanned aerial vehicle in non-trivial settings, by leveraging a manipulator arm mounted on a ground robot, acting as a versatile mobile launch platform. As real-world deployment scenarios for micro aerial vehicles such as searchand- rescue operations often entail exploration and navigation of challenging environments including uneven terrain, cluttered spaces, or even constrained openings and passageways, an often arising problem is that of ensuring a safe take-off location, or safely fitting through narrow openings while in flight. By facilitating launching from the manipulator end-effector, a 6- DoF controllable take-off pose within the arm workspace can be achieved, which allows to properly position and orient the aerial vehicle to initialize the autonomous flight portion of a mission. To accomplish this, we propose a sampling-based planner that respects a) the kinematic constraints of the ground robot / manipulator / aerial robot combination, b) the geometry of the environment as autonomously mapped by the ground robots perception systems, and c) accounts for the aerial robot expected dynamic motion during takeoff. The goal of the proposed planner is to ensure autonomous collision-free initialization of an aerial robotic exploration mission, even within a cluttered constrained environment. At more »
- Award ID(s):
- 2008904
- Publication Date:
- NSF-PAR ID:
- 10296731
- Journal Name:
- 2021 IEEE Conference on Aerospace
- Sponsoring Org:
- National Science Foundation
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