Motion model binary switch for MonoSLAM

Akin Tatoglu, Kishore Pochiraju

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

3 Scopus citations

Abstract

Current Monocular Simultaneous Localization and Mapping (MonoSLAM) methodologies use constant velocity and smooth motion assumptions. If the motion consists of rapid accelerations, decelerations or stops, the position estimates become erroneous and unstable. Mobile robots require frequent stops due to mission dictated or safety reasons. With the objective of using MonoSLAM to localize a mobile robot, we determined the effectiveness of trajectory estimation for a typical robot moving with constant velocity and stopping to execute missions. Experiments were performed with a camera mounted on a 3-axis translational robot and several path profiles with brief stops were executed. The trajectory estimated with a MonoSLAM algorithm is compared with the known motion profile. As the stop causes significant error and drift in the position estimates, we modified the constant velocity motion model to incorporate a stop detection method. An optical flow based stop detection model was formulated and implemented in conjunction with MonoSLAM. Velocity update is modified when a stop or start is detected by optical flow. By adaptively switching between constant velocity and stop models, the trajectory estimate is seen to be more accurate and stable after an intermittent stop. Details of the adaptive switching method and the performance of the modified MonoSLAM are described in this paper.

Original languageEnglish
Title of host publication2015 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2015
ISBN (Electronic)9781479986439
DOIs
StatePublished - 15 Jul 2015
Event2015 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2015 - Farmingdale, United States
Duration: 1 May 2015 → …

Publication series

Name2015 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2015

Conference

Conference2015 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2015
Country/TerritoryUnited States
CityFarmingdale
Period1/05/15 → …

Keywords

  • MonoSLAM
  • affine optical flow
  • localization
  • motion model

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