Joint optimization of robot design and motion parameters using the implicit function theorem

Sehoon Ha, Stelian Coros, Alexander Alspach, Joohyung Kim, Katsu Yamane

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We present a novel computational approach to optimizing the morphological design of robots. Our framework takes as input a parameterized robot design and a motion plan consisting of trajectories for end-effectors, as well as optionally, for its body. The algorithm we propose is used to optimize design parameters, namely link lengths and the placement of actuators, while concurrently adjusting motion parameters such as joint trajectories, actuator inputs, and contact forces. Our key insight is that the complex relationship between design and motion parameters can be established via sensitivity analysis if the robot's movements are modeled as spatio-temporal solutions to optimal control problems. This relationship between form and function allows us to automatically optimize robot designs based on specifications expressed as a function of range of motion or actuator forces. We evaluate our model by computationally optimizing two simulated robots that employ linear actuators: a manipulator and a large quadruped. We further validate our framework by optimizing the design of a small quadrupedal robot and testing its performance using a hardware implementation.

Original languageEnglish (US)
Title of host publicationRobotics
Subtitle of host publicationScience and Systems XIII, RSS 2017
EditorsSiddhartha Srinivasa, Nora Ayanian, Nancy Amato, Scott Kuindersma
PublisherMIT Press Journals
ISBN (Electronic)9780992374730
StatePublished - 2017
Externally publishedYes
Event2017 Robotics: Science and Systems, RSS 2017 - Cambridge, United States
Duration: Jul 12 2017Jul 16 2017

Publication series

NameRobotics: Science and Systems
ISSN (Electronic)2330-765X


Conference2017 Robotics: Science and Systems, RSS 2017
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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