2015
DOI: 10.3390/s150304925
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Sensor Data Fusion for Body State Estimation in a Bipedal Robot and Its Feedback Control Application for Stable Walking

Abstract: We report on a sensor data fusion algorithm via an extended Kalman filter for estimating the spatial motion of a bipedal robot. Through fusing the sensory information from joint encoders, a 6-axis inertial measurement unit and a 2-axis inclinometer, the robot’s body state at a specific fixed position can be yielded. This position is also equal to the CoM when the robot is in the standing posture suggested by the detailed CAD model of the robot. In addition, this body state is further utilized to provide sensor… Show more

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Cited by 7 publications
(4 citation statements)
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“…Position sensors on the motors provide data during locomotion that are key for both current state identification during the gait and biped robot further steps planning. Chen et al [146] described a joint sensor system with a Kalman filter for the feedback control of the walking robot.…”
Section: Sensor Systemsmentioning
confidence: 99%
See 1 more Smart Citation
“…Position sensors on the motors provide data during locomotion that are key for both current state identification during the gait and biped robot further steps planning. Chen et al [146] described a joint sensor system with a Kalman filter for the feedback control of the walking robot.…”
Section: Sensor Systemsmentioning
confidence: 99%
“…Zieli ńska described four coupled oscillators generating real-time outputs similar to human gait [57]. Chen et al [146] presented sensor data fusion for the state of body estimation in stable walking using feedback control. Klein and Lewis provided a neuro robotic model based on Golgi tendon organs, and spiking neural networks [147].…”
mentioning
confidence: 99%
“…Moreover, this technique requires the integration of force sensing modules in the robot foot, which may not always be available/feasible. Another alternative method to compute the ZMP is from the variation of different joint angles 24,25 . In such technique, the robot is mainly modeled by an inverted pendulum system with simple joints and links [26][27][28][29] .…”
Section: Introductionmentioning
confidence: 99%
“…Robot-environment interaction is common in robotics applications [ 1 ], such as grasping and manipulating objects [ 2 ], bipedal walking [ 3 ], etc . A tactile sensors is a device or system capable of measuring the contact parameters between the sensor and an object [ 4 ], such as contact force and slippage, and provide an important approach for robots to sense the environment, like the sense of touch in humans.…”
Section: Introductionmentioning
confidence: 99%