Admittance Controller with Spatial Modulation for Assisted Locomotion using a Smart Walker

Mario F. Jiménez, Matias Monllor, Anselmo Frizera, Teodiano Bastos, Flavio Roberti, Ricardo Carelli

Research output: Contribution to journalArticlepeer-review

35 Scopus citations


Smart Walkers are robotic devices that may be used to improve the stability in people with lower limb weakness or poor balance. Such devices may also offer support for cognitive disabilities and for people that cannot safely use conventional walkers. This paper presents an admittance controller that generates haptic signals to induce the tracking of a predetermined path. During use, when deviating from such path, the method proposed here varies the damping parameter of an admittance controller by means of a spatial modulation technique, resulting in a haptic feedback, which is perceived by the user as a difficult locomotion in wrong direction. The UFES’s Smart Walker uses a multimodal cognitive interaction composed by a haptic feedback, and a visual interface with two LEDs to indicate the correct/desired direction when necessary. The controller was validated in two experiments. The first one consisted of following a predetermined path composed of straight segments. The second experiment consisted of finding a predetermined path starting from a position outside of such path. When haptic feedback was used, the kinematic estimation error was around 0.3 (± 0.13) m and the force applied to move the walker was approximately 5 kgf. When the multimodal interaction was performed with the haptic and visual interfaces, the kinematic estimation error decreased to 0.16 (± 0.03) m, and the force applied dropped to around 1 kgf, which can be seen as an important improvement on assisted locomotion.

Original languageEnglish (US)
Pages (from-to)621-637
Number of pages17
JournalJournal of Intelligent and Robotic Systems: Theory and Applications
Issue number3-4
StatePublished - Jun 14 2019
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering


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