Modular robots morphology transformation and task execution / Chao Liu.

Format:

Book

Thesis/Dissertation

Author/Creator:

Liu, Chao, author.

Contributor:

Yim, Mark, degree supervisor.

University of Pennsylvania. Department of Mechanical Engineering and Applied Mechanics, degree granting institution.

Language:

English

Subjects (All):

Robotics.

Morphology.

Mechanical engineering and applied mechanics--Penn dissertations.

Penn dissertations--Mechanical engineering and applied mechanics.

Local Subjects:

Robotics.

Morphology.

Mechanical engineering and applied mechanics--Penn dissertations.

Penn dissertations--Mechanical engineering and applied mechanics.

Genre:

Academic theses.

Physical Description:

1 online resource (268 pages)

Contained In:

Dissertations Abstracts International 83-03B.

Place of Publication:

[Philadelphia, Pennsylvania] : University of Pennsylvania ; Ann Arbor : ProQuest Dissertations & Theses, 2021.

Language Note:

English

System Details:

Mode of access: World Wide Web.

text file

Summary:

Self-reconfigurable modular robots are composed of a small set of modules with uniform docking interfaces. Different from conventional robots that are custom-built and optimized for specific tasks, modular robots are able to adapt to many different activities and handle hardware and software failures by rearranging their components. This reconfiguration capability allows these systems to exist in a variety of morphologies, and the introduced flexibility enables self-reconfigurable modular robots to handle a much wider range of tasks, but also complicates the design, control, and planning. This thesis considers a hierarchy framework to deploy modular robots in the real world: the robot first identifies its current morphology, then reconfigures itself into a new morphology if needed, and finally executes either manipulation or locomotion tasks. A reliable system architecture is necessary to handle a large number of modules. The number of possible morphologies constructed by modules increases exponentially as the number of modules grows, and these morphologies usually have many degrees of freedom with complex constraints. In this thesis, hardware platforms and several control methods and planning algorithms are developed to build this hierarchy framework leading to the system-level deployment of modular robots, including a hybrid modular robot (SMORES-EP) and a modular truss robot (VTT). Graph representations of modular robots are introduced as well as several algorithms for morphology identification. Efficient mobile-stylereconfiguration strategies are explored for hybrid modular robots, and a real-time planner based on optimal control is developed to perform dexterous manipulation tasks. For modular truss robots, configuration space is studied and a hybrid planning framework (sampling-based and search-based) is presented to handle reconfiguration activities. A non-impact rolling locomotion planner is then developed to drive an arbitrary truss robot in an environment.

Notes:

Source: Dissertations Abstracts International, Volume: 83-03, Section: B.

Advisors: Yim, Mark; Committee members: Taylor, Camillo J.; Sung, Cynthia.

Department: Mechanical Engineering and Applied Mechanics.

Ph.D. University of Pennsylvania 2021.

Local Notes:

School code: 0175

ISBN:

9798535571133

Access Restriction:

Restricted for use by site license.

This item must not be sold to any third party vendors.