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Interactive Multimodal Recognition Of Household Objects by a Robot
| Content Provider | Semantic Scholar |
|---|---|
| Author | Bergquist, Taylor Ohiri, Ugonna Schenck, Conner Sinapov, Jivko Griffith, Shane Stoytchev, Alex |
| Copyright Year | 2009 |
| Abstract | This paper proposes a system for interactive multimodal recognition of household objects by a robot. Robots will need as many senses as possible in order to interact with these objects in our humanoid environments. A robot was equipped to observe both proprioceptive and auditory sensory input while performing five different behaviors on the objects in its environment. The robot learned from the sound produced by the object and from the change in joint torque during each interaction. The results show that an interactive approach to object recognition using both auditory and proprioceptive feedback performs better than auditory feedback alone. We conclude that a multimodal approach to object recognition is advantageous because one mode of sensory input may uncover important features that other modes cannot sense. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.vrac.iastate.edu/wp-content/uploads/2014/11/REU_Interactive_Mutimodal_Recognition_Of_Household_Objects_by_a_Robot_Research_Paper_copy__2_.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
