Dec 11, 2019 · In this paper, we use CASNET to learn generalizable control policies for two separate classes of robots: planer-manipulators and crawling robots.

In this regard, we propose a novel approach based on recurrent neural networks which learns modular representations of robots in tandem with a higher level meta ...

A new framework named CASNET to learn control policies that generalize over similar robot types with different morphologies is proposed, demonstrating the ...

Abstract:This paper proposes a new framework named CASNET to learn control policies that generalize over similar robot types with different morphologies.

Zero-shot generalization using cascaded system-representations. A Malik. arXiv preprint arXiv:1912.05501, 2019. 2, 2019 ; A generic decentralized gait generator ...

Our empirical results using state of the art on and off policy learning algorithms show that on average, CASNET agent achieves zero shot optimal performance ( ...

Nov 1, 2024 · The key idea is that a neural network can learn explicit representations of space—similar to those found in the primate dorsal stream—by ...

Zero-shot generalization using cascaded system-representations. A Malik. arXiv preprint arXiv:1912.05501, 2019. 2, 2019 ; A generic decentralized gait generator ...

Dec 17, 2019 · Efficient Robotic Task Generalization Using Deep Model Fusion ... Zero-shot generalization using cascaded system-representations by ...

In this work, we conduct experiments that show that leveraging the robot URDFs and aligning the action spaces could enable even a single-robot specialist policy.