Search for: All records

This paper presents the design and control of a ballbot drivetrain that aims to achieve high agility, minimal footprint, and high payload capacity while maintaining dynamic stability. Two hardware platforms and analytical models were developed to test design and control methodologies. The fullscale ballbot prototype (MiaPURE) was constructed using offthe- shelf components and designed to have agility, footprint, and balance similar to that of a walking human. The planar inverted pendulum testbed (PIPTB) was developed as a reduced-order testbed for quick validation of system performance. We then proposed a simple yet robust cascaded LQR-PI controller to balance and maneuver the ballbot drivetrain with a heavy payload. This is crucial because the drivetrain is often subject to high stiction due to elastomeric components in the torque transmission system. This controller was first tested in the PIPTB to compare with traditional LQR and cascaded PI-PD controllers, and then implemented in the ballbot drivetrain. The MiaPURE drivetrain was able to carry a payload of 60 kg, achieve a maximum speed of 2.3 m/s, and come to a stop from a speed of 1.4 m/s in 2 seconds in a selected translation direction. Finally, we demonstrated the omnidirectional movement of the ballbot drivetrain in an indoor environment as a payload-carrying robot and a human-riding mobility device. Our experiments demonstrated the feasibility of using the ballbot drivetrain as a universal mobility platform with agile movements, minimal footprint, and high payload capacity using our proposed design and control methodologies. 

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. 

A novel wheelchair called PURE ( Personalized Unique Rolling Experience) that uses hands hands-free (HF) torso leanlean-to -steer control has been developed for manual wheelchair users (mWCUs). PURE addresses limitations of current wheelchairs, such as the in ability to use both hands for life experiences instead of propulsion. PURE uses a ball ball-based robot drivetrain to offer a compactcompact, selfself- balancing , omnidirectional mobile device. A custom sensor system convertconverts rider torso motions into direction and speed commands to control PURE, which is especially useful if a rider has minimal torso range of motion. We explored whether PURE’s HF control performed as well as a traditional joystick (JS) human human- robot interface and mWCUsmWCUs, performed as well as able able-bodied users (ABUs). 10 mWCUs and 10 ABUs were trained and tested to drive PURE through courses replicating indoor settingssettings. Each participant adjusted ride sensitivity settings for both HF and JS control . Repeated Repeated-measures MANOVA tests suggested that the number of collisions collisions, completion time time, NASA TLX scores except physical demand , and index of performance performances were similar for HF and JS control and between mWCUs and ABUs for all sections. Th is suggestsuggests that PURE is effective for controlling this new omnidirectional wheelchair by only using torso motion thus leaving both hands to be used for other tasks during propulsion propulsion. 

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).