Stochastic Optimal Control for Modeling Reaching Movements in the Presence of Obstacles: Theory and Simulation

Arun Kumar Singh, Sigal Berman, Ilana Nisky

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In many human-in-the-Ioop robotic applications such as robot-assisted surgery and remote teleoperation, predicting the intended motion of the human operator may be useful for successful implementation of shared control, guidance virtual fixtures, and predictive control. Developing computational models of human movements is a critical foundation for such motion prediction frameworks. With this motivation, we present a computational framework for modeling reaching movements in the presence of obstacles. We propose a stochastic optimal control framework that consists of probabilistic collision avoidance constraints and a cost function that trades-off between effort and end-state variance in the presence of a signal-dependent noise. First, we present a series of reformulations to convert the original non-linear and non-convex optimal control into a parametric quadratic programming problem. We show that the parameters can be tuned to model various collision avoidance strategies, thereby capturing the quintessential variability associated with human motion. Then, we present a simulation study that demonstrates the complex interaction between avoidance strategies, control cost, and the probability of collision avoidance. For ease of exposition, our simulations are restricted to 2D trajectories. The proposed framework can benefit a variety of applications that require teleoperation in cluttered spaces, including robot-assisted surgery. In addition, it can also be viewed as a new optimizer which produces smooth and probabilistically-safe trajectories under signal dependent noise.

Original languageEnglish
Title of host publicationBIOROB 2018 - 7th IEEE International Conference on Biomedical Robotics and Biomechatronics
PublisherIEEE Computer Society
Pages997-1004
Number of pages8
Volume2018-August
ISBN (Electronic)9781538681831
DOIs
StatePublished - 9 Oct 2018
Event7th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BIOROB 2018 - Enschede, Netherlands
Duration: 26 Aug 201829 Aug 2018

Conference

Conference7th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BIOROB 2018
Country/TerritoryNetherlands
CityEnschede
Period26/08/1829/08/18

ASJC Scopus subject areas

  • Artificial Intelligence
  • Biomedical Engineering
  • Mechanical Engineering

Fingerprint

Dive into the research topics of 'Stochastic Optimal Control for Modeling Reaching Movements in the Presence of Obstacles: Theory and Simulation'. Together they form a unique fingerprint.

Cite this