Whole arm planning for a soft and highly compliant 2D robotic manipulator
Name
Marchese Katzschmann Rus - 2014 - Whole Arm Planning for a Soft and Highly Compliant 2D Robotic Manipulator (002).pdf
Size
8.41 MB
Format
Adobe PDF
Checksum (MD5)
2ab11b1ec3e1cace7167e83771029b6f
Author(s)
Marchese, Andrew Dominic
Katzschmann, Robert Kevin
Rus, Daniela L
Date Issued
September 2014
Journal
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Marchese, Andrew D., Robert K. Katzschmann, and Daniela Rus. “Whole Arm Planning for a Soft and Highly Compliant 2D Robotic Manipulator.” 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (September 2014).
Version
Author's final manuscript
Abstract
Soft continuum manipulators have the advantage of being more compliant and having more degrees of freedom than rigid redundant manipulators. This attribute should allow soft manipulators to autonomously execute highly dexterous tasks. However, current approaches to motion planning, inverse kinematics, and even design limit the capacity of soft manipulators to take full advantage of their inherent compliance. We provide a computational approach to whole arm planning for a soft planar manipulator that advances the arm's end effector pose in task space while simultaneously considering the arm's entire envelope in proximity to a confined environment. The algorithm solves a series of constrained optimization problems to determine locally optimal inverse kinematics. Due to inherent limitations in modeling the kinematics of a highly compliant soft robot and the local optimality of the planner's solutions, we also rely on the increased softness of our newly designed manipulator to accomplish the whole arm task, namely the arm's ability to harmlessly collide with the environment. We detail the design and fabrication of the new modular manipulator as well as the planner's central algorithm. We experimentally validate our approach by showing that the robotic system is capable of autonomously advancing the soft arm through a pipe-like environment in order to reach distinct goal states.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/IROS.2014.6942614
