MORE | Fall 2021
Extended Kalman Filter Based Sensor Fusion for State Estimation of a Soft Robot Arm
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.
Robotics and autonomous systems
Hometown: Pleasant Grove, Utah, United States
Graduation date: Spring 2022