9,556 research outputs found
Accurate Feature Extraction and Control Point Correction for Camera Calibration with a Mono-Plane Target
The paper addresses two problems related to 3D camera calibration using a single mono-plane calibration target with circular control marks. The first problem is how to compute accurately the locations of the features (ellipses) in images of the target. Since the structure of the control marks is known beforehand, we propose to use a shape-specific searching technique to find the optimal locations of the features. Our experiments have shown this technique generates more accurate feature locations than the state-of-the-art ellipse extraction methods. The second problem is how to refine the control mark locations with unknown manufacturing errors. We demonstrate in a case study, where the control marks are laser printed on a A4 paper, that the manufacturing errors of the control marks can be compensated to a good extent so that the remaining calibration errors are reduced significantly. 1
Robust Legged Robot State Estimation Using Factor Graph Optimization
Legged robots, specifically quadrupeds, are becoming increasingly attractive
for industrial applications such as inspection. However, to leave the
laboratory and to become useful to an end user requires reliability in harsh
conditions. From the perspective of state estimation, it is essential to be
able to accurately estimate the robot's state despite challenges such as uneven
or slippery terrain, textureless and reflective scenes, as well as dynamic
camera occlusions. We are motivated to reduce the dependency on foot contact
classifications, which fail when slipping, and to reduce position drift during
dynamic motions such as trotting. To this end, we present a factor graph
optimization method for state estimation which tightly fuses and smooths
inertial navigation, leg odometry and visual odometry. The effectiveness of the
approach is demonstrated using the ANYmal quadruped robot navigating in a
realistic outdoor industrial environment. This experiment included trotting,
walking, crossing obstacles and ascending a staircase. The proposed approach
decreased the relative position error by up to 55% and absolute position error
by 76% compared to kinematic-inertial odometry.Comment: 8 pages, 12 figures. Accepted to RA-L + IROS 2019, July 201
FlightGoggles: A Modular Framework for Photorealistic Camera, Exteroceptive Sensor, and Dynamics Simulation
FlightGoggles is a photorealistic sensor simulator for perception-driven
robotic vehicles. The key contributions of FlightGoggles are twofold. First,
FlightGoggles provides photorealistic exteroceptive sensor simulation using
graphics assets generated with photogrammetry. Second, it provides the ability
to combine (i) synthetic exteroceptive measurements generated in silico in real
time and (ii) vehicle dynamics and proprioceptive measurements generated in
motio by vehicle(s) in a motion-capture facility. FlightGoggles is capable of
simulating a virtual-reality environment around autonomous vehicle(s). While a
vehicle is in flight in the FlightGoggles virtual reality environment,
exteroceptive sensors are rendered synthetically in real time while all complex
extrinsic dynamics are generated organically through the natural interactions
of the vehicle. The FlightGoggles framework allows for researchers to
accelerate development by circumventing the need to estimate complex and
hard-to-model interactions such as aerodynamics, motor mechanics, battery
electrochemistry, and behavior of other agents. The ability to perform
vehicle-in-the-loop experiments with photorealistic exteroceptive sensor
simulation facilitates novel research directions involving, e.g., fast and
agile autonomous flight in obstacle-rich environments, safe human interaction,
and flexible sensor selection. FlightGoggles has been utilized as the main test
for selecting nine teams that will advance in the AlphaPilot autonomous drone
racing challenge. We survey approaches and results from the top AlphaPilot
teams, which may be of independent interest.Comment: Initial version appeared at IROS 2019. Supplementary material can be
found at https://flightgoggles.mit.edu. Revision includes description of new
FlightGoggles features, such as a photogrammetric model of the MIT Stata
Center, new rendering settings, and a Python AP
A biaxial apparatus for the study of heterogeneous and intermittent strains in granular materials
We present an experimental apparatus specifically designed to investigate the
precursors of failure in granular materials. A sample of granular material is
placed between a latex membrane and a glass plate. A confining effective
pressure is applied by applying vacuum to the sample. Displacement-controlled
compression is applied in the vertical direction, while the specimen deforms in
plane strain. A Diffusing Wave Spectroscopy visualization setup gives access to
the measurement of deformations near the glass plate. After describing the
different parts of this experimental setup, we present a demonstration
experiment where extremely small (of order ) heterogeneous strains are
measured during the loading process
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