9,660 research outputs found
3D head tracking using normal flow constraints in a vehicle environment
Head tracking is a key component in applications such as human computer interaction, person monitoring, driver monitoring, video conferencing, and object-based compression. The motion of a driver’s head can tell us a lot about his/her mental state; e.g. whether he/she is drowsy, alert, aggressive,
comfortable, tense, distracted, etc. This paper reviews an optical flow based method to track the head pose, both orientation and position, of a person and presents results from real world data recorded in a car environment
Rigid Body Motion Estimation based on the Lagrange-d'Alembert Principle
Stable estimation of rigid body pose and velocities from noisy measurements,
without any knowledge of the dynamics model, is treated using the
Lagrange-d'Alembert principle from variational mechanics. With body-fixed
optical and inertial sensor measurements, a Lagrangian is obtained as the
difference between a kinetic energy-like term that is quadratic in velocity
estimation error and the sum of two artificial potential functions; one
obtained from a generalization of Wahba's function for attitude estimation and
another which is quadratic in the position estimate error. An additional
dissipation term that is linear in the velocity estimation error is introduced,
and the Lagrange-d'Alembert principle is applied to the Lagrangian with this
dissipation. This estimation scheme is discretized using discrete variational
mechanics. The presented pose estimator requires optical measurements of at
least three inertially fixed landmarks or beacons in order to estimate
instantaneous pose. The discrete estimation scheme can also estimate velocities
from such optical measurements. In the presence of bounded measurement noise in
the vector measurements, numerical simulations show that the estimated states
converge to a bounded neighborhood of the actual states.Comment: My earlier submitted manuscript (arXiv:1508.07671), is an extended
version of this work, containing detailed proofs and more elaborated
numerical simulations, currently under review in Automatica. This paper will
be cited in the extended journal version (arXiv:1508.07671) upon publicatio
Towards Efficient Full Pose Omnidirectionality with Overactuated MAVs
Omnidirectional MAVs are a growing field, with demonstrated advantages for
aerial interaction and uninhibited observation. While systems with complete
pose omnidirectionality and high hover efficiency have been developed
independently, a robust system that combines the two has not been demonstrated
to date. This paper presents VoliroX: a novel omnidirectional vehicle that can
exert a wrench in any orientation while maintaining efficient flight
configurations. The system design is presented, and a 6 DOF geometric control
that is robust to singularities. Flight experiments further demonstrate and
verify its capabilities.Comment: 10 pages, 6 figures, ISER 2018 conference submissio
A Unified Dissertation on Bearing Rigidity Theory
This work focuses on the bearing rigidity theory, namely the branch of
knowledge investigating the structural properties necessary for multi-element
systems to preserve the inter-units bearings when exposed to deformations. The
original contributions are twofold. The first one consists in the definition of
a general framework for the statement of the principal definitions and results
that are then particularized by evaluating the most studied metric spaces,
providing a complete overview of the existing literature about the bearing
rigidity theory. The second one rests on the determination of a necessary and
sufficient condition guaranteeing the rigidity properties of a given
multi-element system, independently of its metric space
Observability analysis and optimal sensor placement in stereo radar odometry
© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Localization is the key perceptual process closing the loop of autonomous navigation, allowing self-driving vehicles to operate in a deliberate way. To ensure robust localization, autonomous vehicles have to implement redundant estimation processes, ideally independent in terms of the underlying physics behind sensing principles. This paper presents a stereo radar odometry system, which can be used as such a redundant system, complementary to other odometry estimation processes, providing robustness for long-term operability. The presented work is novel with respect to previously published methods in that it contains: (i) a detailed formulation of the Doppler error and its associated uncertainty; (ii) an observability analysis that gives the minimal conditions to infer a 2D twist from radar readings; and (iii) a numerical analysis for optimal vehicle sensor placement. Experimental results are also detailed that validate the theoretical insights.Peer ReviewedPostprint (author's final draft
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