RBE PhD Dissertation Defense: Shou-Shan Chiang | Real-time and Customizable Inverse Kinematics for Extensible Multisection Continuum Robots: SLInKi and AMoRPH Algorithms

Friday, December 8, 2023
3:30 p.m. to 4:30 p.m.
Floor/Room #
Room 203
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RBE PhD Dissertation Defense

Shou-Shan Chiang

Real-time and Customizable Inverse Kinematics for Extensible Multisection Continuum Robots: SLInKi and AMoRPH Algorithms

December 8th, 2023

3:30 PM - 4:30 PM 

Location: IS room 203

Abstract:  Extensible multisection continuum robots are characterized by their continuous and compliant structures, which provide them with superior adaptability and flexibility compared to traditional robots. Nonetheless, the complexity of their kinematics and inverse kinematics presents significant challenges. This study addresses these challenges by introducing two innovative algorithms for inverse kinematics: SLInKi and AMoRPH. SLInKi is a hybrid approach that combines state lattice searching algorithms, exFABRIKc, and analytical solvers. Its main focus is on real-time solution and optimization of shape and motion smoothness, allowing for customization. On the other hand, AMoRPH is a novel analytical solver that utilizes a virtual linkage model in order to efficiently solve the 5 degree-of-freedom inverse kinematics problem and find balanced and smooth solutions. When faced with non-uniform cases and obstacles, segment addition and geometry adjustments are employed. This algorithm effectively addresses the inverse kinematics problem with speed, accuracy, and versatility. The validity of both algorithms is demonstrated through simulations and experiments, which showcase their effectiveness in real-time control, precise tracking, and obstacle avoidance for continuum robots.
 

Advisor:

Professor Cagdas Onal, Worcester Polytechnic Institute (WPI)

Committee: 

Professor Berk Calli, Worcester Polytechnic Institute (WPI)

Professor Jing Xiao, Worcester Polytechnic Institute (WPI)

Professor Yunus Dogan Telliel, Worcester Polytechnic Institute (WPI)

Audience(s)

Department(s):

Robotics Engineering