Representing, learning, and controlling complex object interactions
We present a framework for representing scenarios with complex object interactions, where a robot cannot directly interact with the object it wishes to control and must instead influence it via intermediate objects. For instance, a robot learning to drive a car can only change the car’s pose indirec...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer US
2018
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| Online Access: | http://hdl.handle.net/1721.1/115928 https://orcid.org/0000-0002-7085-3880 |