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Abstract There have been significant advances in biosignal extraction techniques to drive external biomechatronic devices or to use as inputs to sophisticated human machine interfaces. The control signals are typically derived from biological signals such as myoelectric measurements made either from the surface of the skin or subcutaneously. Other biosignal sensing modalities are emerging. With improvements in sensing modalities and control algorithms, it is becoming possible to robustly control the target position of an end-effector. It remains largely unknown to what extent these improvements can lead to naturalistic human-like movement. In this paper, we sought to answer this question. We utilized a sensing paradigm called sonomyography based on continuous ultrasound imaging of forearm muscles. Unlike myoelectric control strategies which measure electrical activation and use the extracted signals to determine the velocity of an end-effector; sonomyography measures muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Previously, we showed that users were able to accurately and precisely perform a virtual target acquisition task using sonomyography. In this work, we investigate the time course of the control trajectories derived from sonomyography. We show that the time course of the sonomyography-derived trajectories that users take to reach virtual targets reflect the trajectories shown to be typical for kinematic characteristics observed in biological limbs. Specifically, during a target acquisition task, the velocity profiles followed a minimum jerk trajectory shown for point-to-point arm reaching movements, with similar time to target. In addition, the trajectories based on ultrasound imaging result in a systematic delay and scaling of peak movement velocity as the movement distance increased. We believe this is the first evaluation of similarities in control policies in coordinated movements in jointed limbs, and those based on position control signals extracted at the individual muscle level. These results have strong implications for the future development of control paradigms for assistive technologies.
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This content will become publicly available on July 8, 2026
End-Effector Position Estimation on Off-Road Vehicles Using IMUs
Estimating the position of the bucket or tool on an agricultural/construction vehicle is becoming increasingly important to enable operator assistance such as automation of repetitive movements. Such end-effector position estimation is normally done through measurement of individual actuator’s movements inside kinematic linkage mechanisms that move the end-effectors. This paper develops an alternate inertial measurement unit (IMU) based end-effector position estimation system that offers significant advantages of low cost and easy installation. An IMU located on a rotating linkage in a mechanism is used to estimate the angular motion of the linkage. Key challenges arise from the fact that the accelerometer signals of the IMU experience significant disturbances from dynamic accelerations and from vehicle and terrain-induced vibrations. First, an adaptive feedforward algorithm is used to remove the influence of vibrations on the accelerometer signals. Then a nonlinear observer is utilized to combine accelerometer and gyroscope signals and reject the influence of vehicle accelerations. Experimental results are presented from a laboratory test rig and preliminary experimental results from a full-scale tracked skid steer loader vehicle. The results show that an accuracy better than 1 degree in linkage orientation estimation is achieved in the presence of vibration disturbances.
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- Award ID(s):
- 2329798
- PAR ID:
- 10635092
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3315-6937-2
- Page Range / eLocation ID:
- 4591 to 4596
- Format(s):
- Medium: X
- Location:
- Denver, CO, USA
- Sponsoring Org:
- National Science Foundation
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