SegVisRL: Visuomotor Development for a Lunar Rover for Hazard Avoidance using Camera Images

no code implementations • 26 Mar 2021 • Tamir Blum, Gabin Paillet, Watcharawut Masawat, Mickael Laine, Kazuya Yoshida

The visuomotor system of any animal is critical for its survival, and the development of a complex one within humans is large factor in our success as a species on Earth.

RL STaR Platform: Reinforcement Learning for Simulation based Training of Robots

1 code implementation • 21 Sep 2020 • Tamir Blum, Gabin Paillet, Mickael Laine, Kazuya Yoshida

Reinforcement learning (RL) is a promising field to enhance robotic autonomy and decision making capabilities for space robotics, something which is challenging with traditional techniques due to stochasticity and uncertainty within the environment.

Decision Making reinforcement-learning +1

PPMC RL Training Algorithm: Rough Terrain Intelligent Robots through Reinforcement Learning

1 code implementation • 2 Mar 2020 • Tamir Blum, Kazuya Yoshida

To the best of our knowledge, this is the first paper to introduce a generic training algorithm teaching generalized PPMC in rough environments to any robot, with just the use of reinforcement learning.

reinforcement-learning Reinforcement Learning (RL)

Deep Learned Path Planning via Randomized Reward-Linked-Goals and Potential Space Applications

1 code implementation • 13 Sep 2019 • Tamir Blum, William Jones, Kazuya Yoshida

Space exploration missions have seen use of increasingly sophisticated robotic systems with ever more autonomy.