Search ETDs:
Design of Stochastic Neural-inspired Dynamical Architectures: Coordination and Control of Hyper-redundant Robots
Horchler, Andrew de Salle

2016, Doctor of Philosophy, Case Western Reserve University, EMC - Mechanical Engineering.
Effective control of soft and hyper-redundant devices, such as worm-like robots, requires many degrees of freedom to be coordinated while adapting the sequential pattern of activity based on sensory feedback. A striking feature of biological pattern generators is their ability to respond immediately to multi-sensory perturbations by modulating the dwell time at a particular phase of activity without disrupting overall coordination. This dissertation presents new mathematical tools for the design and analysis of a dynamical architecture that can be used to responsively coordinate many degrees of freedom: stable heteroclinic channels (SHCs). For SHC cycles, the addition of stochastic noise results in oscillation with a regular mean period. A new soft robot, Compliant Modular Mesh Worm, which utilizes individually actuated segments to produce peristaltic locomotion, has been constructed as a platform to evaluate SHC control. The robot's modular mesh allows components to be easily interchanged to vary stiffness. Experiments were performed to characterize the actuated mesh and study how the interaction between friction, compliance, and the precision of segment control impacts locomotion performance. A real time SHC controller that allows predictable noise-driven variability of the robot's locomotion pattern was developed and evaluated. These results will be useful for the design and control of future peristaltic devices.
Roger Quinn (Advisor)
Hillel Chiel (Advisor)
Joseph Mansour (Committee Member)
Cenk Cavusoglu (Committee Member)
163 p.

Recommended Citations

Hide/Show APA Citation

Horchler, A. (2016). Design of Stochastic Neural-inspired Dynamical Architectures: Coordination and Control of Hyper-redundant Robots. (Electronic Thesis or Dissertation). Retrieved from https://etd.ohiolink.edu/

Hide/Show MLA Citation

Horchler, Andrew. "Design of Stochastic Neural-inspired Dynamical Architectures: Coordination and Control of Hyper-redundant Robots." Electronic Thesis or Dissertation. Case Western Reserve University, 2016. OhioLINK Electronic Theses and Dissertations Center. 18 Dec 2017.

Hide/Show Chicago Citation

Horchler, Andrew "Design of Stochastic Neural-inspired Dynamical Architectures: Coordination and Control of Hyper-redundant Robots." Electronic Thesis or Dissertation. Case Western Reserve University, 2016. https://etd.ohiolink.edu/

Files

Horchler_Dissertation_2016.pdf (107.74 MB) View|Download