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A hands-free (HF) lean-to-steer control concept that uses torso motions is demonstrated by navigating a virtual robotic mobility device based on a ball-based robotic (ballbot) wheelchair. A custom sensor system (i.e., Torso-dynamics Estimation System (TES)) was utilized to measure and convert the dynamics of the rider’s torso motions into commands to provide HF control of the robot. A simulation study was conducted to explore the efficacy of the HF controller compared to a traditional joystick (JS) controller, and whether there were differences in performance by manual wheelchair users (mWCUs), who may have reduced torso function, compared to able-bodied users (ABUs). Twenty test subjects (10 mWCUs + 10 ABUs) used the subject-specific adjusted TES while wearing a virtual reality headset and were asked to navigate a virtual human rider on the ballbot through obstacle courses replicating seven indoor environment zones. Repeated measures MANOVA tests assessed performance metrics representing efficiency (i.e., number of collisions), effectiveness (i.e., completion time), comfort (i.e., NASA TLX scores), and robustness (i.e., index of performance). As expected, more challenging zones took longer to complete and resulted in more collisions. An interaction effect was observed such that ABUs had significantly more collisions using JS vs. HF control, while mWCUs had little difference with either interface. All subjects reported greater physical demand was needed for HF control than JS control; although, no users visibly showed or expressed fatigue or exhaustion when using HF control. In general, HF control performed as well as JS control, and mWCUs performed similarly to ABUs.
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Design and Validation of a Torso-Dynamics Estimation System (TES) for Hands-Free Physical Human-Robot Interaction
We designed and validated two interfaces for physical human-robot interaction that utilize torso motions for hands-free navigation control of riding or remote mobile robots. The Torso-dynamics Estimation System (TES), which consisted of an instrumented seat (Force Sensing Seat, FSS) and a wearable sensor (inertial measurement unit, IMU), was developed to quantify the translational and rotational motions of the torso, respectively. The FSS was constructed from six uniaxial loadcells to output 3D resultant forces and torques, which were used to compute the translational movement of the 2D center of pressure (COP) under the seated user. Two versions of the FSS (Gen 1.0 and 2.0) with different loadcell layouts, materials, and manufacturing methods were developed to showcase the versatility of the FSS design and construction. Both FSS versions utilized low-cost components and a simple calibration protocol to correct for dimensional inaccuracies. The IMU, attached on the user’s upper chest, used a proprietary algorithm to compute the 3D torso angles without relying heavily on magnetometers to minimize errors from electromagnetic noises. A validation study was performed on eight test subjects (six able-bodied users and two manual wheelchair users with reduced torso range of motion) to validate TES estimations by comparing them to data collected on a research-grade force plate and motion capture system. TES readings displayed high accuracy (average RMSE of 3D forces, 3D torques, 2D COP, and torso angles were well less than maximum limits of 5N, 5Nm, 10mm, and 6˚, respectively).
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- Award ID(s):
- 2024905
- PAR ID:
- 10548503
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3503-3670-2
- Page Range / eLocation ID:
- 171 to 178
- Format(s):
- Medium: X
- Location:
- Busan, Korea, Republic of
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/RO-MAN57019.2023.10309422
