Date of Award

Fall 10-2016

Embargo Period


Degree Type


Degree Name

Doctor of Philosophy (PhD)


Robotics Institute


Ralph Hollis


This work describes methods for advancing the state of the art in mobile robot navigation and physical Human-Robot Interaction (pHRI). An enabling technology in this effort is the ballbot, a person-sized mobile robot that balances on a ball. This underactuated robot presents unique challenges in planning, navigation, and control; however, it also has significant advantages over conventional mobile robots. The ballbot is omnidirectional and physically compliant. Moving requires the ballbot to lean, but this also gives it the ability to achieve both soft, compliant physical interaction and apply large forces. The work presented in this dissertation demonstrates the ability to navigate cluttered environments with the ballbot. Formulating the system as differentially flat enables fast, analytic trajectory planning. These trajectories are used to plan in the space of static and dynamic obstacles. Leveraging the ballbot’s navigational capabilities, this dissertation also presents a method of physically leading people by the hand. A human subject trial was conducted to assess the feasibility, safety, and comfort of this method. This study was successful, with the ballbot leading participants to multiple goals utilizing an amount of force that users found comfortable. Another area of pHRI explored in this dissertation is assisting people in transition from a seated position to standing. Another user study was conducted to discover how humans help each other out of chairs and how much force they apply. These data were used to design an impedance controller for the ballbot, and this controller was tested and found to deliver equivalent forces to those generated by people. Lastly, this work explores capabilities that could enable the ballbot to navigate through dense crowds of people. A method for detecting collision and estimating external forces was explored. This method was tested and used to modify a costmap. Iteratively updating this costmap and using it to plan trajectories enabled the robot to discover obstacles through collision. Because the ballbot is inherently compliant, these collisions resulted in safe interactions with small forces.