Information-driven Affordance Discovery for Efficient Robotic Manipulation
Pietro Mazzaglia,Taco Cohen,Daniel Dijkman,Pietro Mazzaglia,Taco Cohen,Daniel Dijkman
Robotic affordances, providing information about what actions can be taken in a given situation, can aid robotic manipulation. However, learning about affordances requires expensive large annotated datasets of interactions or demonstrations. In this work, we argue that well-directed interactions with the environment can mitigate this problem and propose an information-based measure to augment the ...
