Feature localization using kinematics and impulsive hybrid optimization

Yoke Peng Leong, Todd Murphey

Research output: Contribution to journalArticlepeer-review


This paper focuses on detecting and localizing a surface feature on an otherwise uniform surface using kinematic data collected during an exploratory procedure. Assuming that characteristics of the feature shape and surface shape are known, a surface feature is detected by performing least squares estimation calculated via impulsive hybrid system optimization. The optimization routine is based on an adjoint formulation which allows the algorithm to be computationally efficient and scalable. This algorithm is also shown to perform well with the presence of measurement noise and model noise, both in simulations and experiments.

Original languageEnglish (US)
Article number6513317
Pages (from-to)957-968
Number of pages12
JournalIEEE Transactions on Automation Science and Engineering
Issue number4
StatePublished - 2013


  • Feature detection
  • feature localization
  • hybrid optimal control
  • tactile estimation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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