Search Results for author: Atsuo Takanishi

Found 3 papers, 1 papers with code

SGD for robot motion? The effectiveness of stochastic optimization on a new benchmark for biped locomotion tasks

1 code implementation9 Oct 2017 Martim Brandao, Kenji Hashimoto, Atsuo Takanishi

In this paper we introduce a new benchmark for trajectory optimization and posture generation of legged robots, using a pre-defined scenario, robot and constraints, as well as evaluation criteria.

Stochastic Optimization

Material Recognition CNNs and Hierarchical Planning for Biped Robot Locomotion on Slippery Terrain

no code implementations27 Jun 2017 Martim Brandao, Yukitoshi Minami Shiguematsu, Kenji Hashimoto, Atsuo Takanishi

In this paper we tackle the problem of visually predicting surface friction for environments with diverse surfaces, and integrating this knowledge into biped robot locomotion planning.

Friction Material Recognition

Perceptual Reward Functions

no code implementations12 Aug 2016 Ashley Edwards, Charles Isbell, Atsuo Takanishi

Reinforcement learning problems are often described through rewards that indicate if an agent has completed some task.

reinforcement-learning Reinforcement Learning (RL)

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