Online trajectory following with position based force/vision control

Olli Alkkiomäki*, Ville Kyrki, Heikki Kälviäinen, Yong Liu, Heikki Handroos

*Corresponding author for this work

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

2 Citations (Scopus)


Robot control in uncertain environments can greatly benefit from sensor based control. Visual sensing allows the robot to examine its surroundings and adapt to the environment. Force offers a complementary sensory modality allowing accurate measurements of local object shape when a tooltip is in contact with the object. In multimodal sensor fusion several sensors measuring different modalities are combined together to give more accurate estimate of the environment. We present a method which fuses force and vision in an extended Kalman filter (EKF). A hybrid force controller is then set up to follow a trajectory based on the estimate from the EKF. The estimate allows a simple proportional force control to track a continuous trajectory reliably, where an unfiltered visual measurement becomes unstable. Experiments verify that the method can increase the stability of control considerably.

Original languageEnglish
Title of host publication2009 International Conference on Advanced Robotics, ICAR 2009
Publication statusPublished - 2009
MoE publication typeA4 Article in a conference publication
Event International Conference on Advanced Robotics - Munich, Germany
Duration: 22 Jun 200926 Jun 2009


Conference International Conference on Advanced Robotics
Abbreviated titleICAR

Fingerprint Dive into the research topics of 'Online trajectory following with position based force/vision control'. Together they form a unique fingerprint.

Cite this