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A mosaic of eyes
Autonomous navigation is a traditional research topic in intelligent robotics and vehicles, which requires a robot to perceive its environment through onboard sensors such as cameras or laser scanners, to enable it to drive to its goal. Most research to date has focused on the development of a large and smart brain to gain autonomous capability for robots. There are three fundamental questions to be answered by an autonomous mobile robot: 1) Where am I going? 2) Where am I? and 3) How do I get there? To answer these basic questions, a robot requires a massive spatial memory and considerable computational resources to accomplish perception, localization, path planning, and control. It is not yet possible to deliver the centralized intelligence required for our real-life applications, such as autonomous ground vehicles and wheelchairs in care centers. In fact, most autonomous robots try to mimic how humans navigate, interpreting images taken by cameras and then taking decisions accordingly. They may encounter the following difficulties
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
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