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Article overview
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Active Perception based Formation Control for Multiple Aerial Vehicles | Rahul Tallamraju
; Eric Price
; Roman Ludwig
; Kamalakar Karlapalem
; Heinrich H. Bülthoff
; Michael J. Black
; Aamir Ahmad
; | Date: |
23 Jan 2019 | Abstract: | Autonomous motion capture (mocap) systems for outdoor scenarios involving
flying or mobile cameras rely on i) a robotic front-end to track and follow a
human subject in real-time while he/she performs physical activities, and ii)
an algorithmic back-end that estimates full body human pose and shape from the
saved videos. In this paper we present a novel front-end for our aerial mocap
system that consists of multiple micro aerial vehicles (MAVs) with only
on-board cameras and computation. In previous work, we presented an approach
for cooperative detection and tracking (CDT) of a subject using multiple MAVs.
However, it did not ensure optimal view-point configurations of the MAVs to
minimize the uncertainty in the person’s cooperatively tracked 3D position
estimate. In this article we introduce an active approach for CDT. In contrast
to cooperatively tracking only the 3D positions of the person, the MAVs can now
actively compute optimal local motion plans, resulting in optimal view-point
configurations, which minimize the uncertainty in the tracked estimate. We
achieve this by decoupling the goal of active tracking as a convex quadratic
objective and non-convex constraints corresponding to angular configurations of
the MAVs w.r.t. the person. We derive it using Gaussian observation model
assumptions within the CDT algorithm. We also show how we embed all the
non-convex constraints, including those for dynamic and static obstacle
avoidance, as external control inputs in the MPC dynamics. Multiple real robot
experiments and comparisons involving 3 MAVs in several challenging scenarios
are presented (video link : this https URL). Extensive simulation
results demonstrate the scalability and robustness of our approach. ROS-based
source code is also provided. | Source: | arXiv, 1901.7813 | Services: | Forum | Review | PDF | Favorites |
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