MORE | Fall 2021

Extended Kalman Filter Based Sensor Fusion for State Estimation of a Soft Robot Arm

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Soft robots could be used directly with humans without the danger that is inherently associated with rigid robots. Currently, one major issue with soft robots is the lack of reliable sensing unless using a motion capture system. This system must be used in a lab. This study investigates a Kalman filter-based sensor fusion of an inertial measuring unit (IMU) sensor along with a wire encoder incorporated with a robot model for accurate state estimation comparable to a motion capture system.

Student researcher

Kyle James Stewart

Robotics and autonomous systems

Hometown: Pleasant Grove, Utah, United States

Graduation date: Spring 2022