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Sensor Filtering And Position Tracking Of A Simulated Planar Bipedal Robot

Sensor Filtering And Position Tracking Of A Simulated Planar Bipedal Robot

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Title: Sensor Filtering And Position Tracking Of A Simulated Planar Bipedal Robot
Author: Rossi, Stefano
Gadsden, Stephen Andrew
Identifier: CSME081
Abstract: The development of a humanoid robot is a very prevalent area of research today. Legged robots have many advantages over wheeled robots on rough or uneven terrains, and are more suitable for an everyday household setting, however they possess many design and control challenges. The spring loaded inverted pendulum (SLIP) is frequently used as a fundamental model to analyze bipedal locomotion. In general, it consists of a stance phase and a flight phase, employing different strategies during these phases to control speed and orientation. Due to the underactuation and hybrid dynamics of bipedal robots, estimating the state of the robot and its appendages can be challenging. In this paper, various Kalman estimation techniques are used to predict the state of a simulated planar SLIP model. The state estimations utilize only simulated sensor data, as if the simulated model was a physical one.
Subject: Mechatronics
Robots and Control
Kalman filter
bipedal robot
legged robot
robotics
simulation
inverted pendulum
SLIP
hybrid dynamics
advanced estimation
sensor filtering
Type: Article
Rights: The copyright for the paper content remains with the author.
URI: http://hdl.handle.net/10315/35229
http://dx.doi.org/10.25071/10315/35229
Published: CSME-SCGM
ISSN: 978-1-77355-023-7
Date: 2018-05

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