Deep Predictive Learning: Motion Learning Concept inspired by Cognitive Robotics
Fuente:
arXiv
Saved in:
| Main Authors: | Suzuki, Kanata, Ito, Hiroshi, Yamada, Tatsuro, Kase, Kei, Ogata, Tetsuya |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Sensorimotor Attention and Language-based Regressions in Shared Latent Variables for Integrating Robot Motion Learning and LLM
by: Suzuki, Kanata, et al.
Published: (2024)
by: Suzuki, Kanata, et al.
Published: (2024)
Proprioception Enhances Vision Language Model in Generating Captions and Subtask Segmentations for Robot Task
by: Suzuki, Kanata, et al.
Published: (2025)
by: Suzuki, Kanata, et al.
Published: (2025)
How to Utilize Failure Demo Data?: Effective Data Selection for Imitation Learning Using Distribution Differences in Attention Mechanism
by: Miyamoto, Kana, et al.
Published: (2026)
by: Miyamoto, Kana, et al.
Published: (2026)
Achieving Faster and More Accurate Operation of Deep Predictive Learning
by: Yoshikawa, Masaki, et al.
Published: (2024)
by: Yoshikawa, Masaki, et al.
Published: (2024)
Compact Task-Aligned Imitation Learning for Laboratory Automation
by: Suzuki, Kanata, et al.
Published: (2026)
by: Suzuki, Kanata, et al.
Published: (2026)
Learning Multimodal Attention for Manipulating Deformable Objects with Changing States
by: Saito, Namiko, et al.
Published: (2023)
by: Saito, Namiko, et al.
Published: (2023)
UF-RNN: Real-Time Adaptive Motion Generation Using Uncertainty-Driven Foresight Prediction
by: Hiruma, Hyogo, et al.
Published: (2025)
by: Hiruma, Hyogo, et al.
Published: (2025)
From Dialogue to Execution: Mixture-of-Agents Assisted Interactive Planning for Behavior Tree-Based Long-Horizon Robot Execution
by: Suzuki, Kanata, et al.
Published: (2026)
by: Suzuki, Kanata, et al.
Published: (2026)
A3RNN: Bi-directional Fusion of Bottom-up and Top-down Process for Developmental Visual Attention in Robots
by: Hiruma, Hyogo, et al.
Published: (2025)
by: Hiruma, Hyogo, et al.
Published: (2025)
Dual-arm Motion Generation for Repositioning Care based on Deep Predictive Learning with Somatosensory Attention Mechanism
by: Miyake, Tamon, et al.
Published: (2024)
by: Miyake, Tamon, et al.
Published: (2024)
Adaptive Motion Generation Using Uncertainty-Driven Foresight Prediction
by: Hiruma, Hyogo, et al.
Published: (2024)
by: Hiruma, Hyogo, et al.
Published: (2024)
Visual Spatial Attention and Proprioceptive Data-Driven Reinforcement Learning for Robust Peg-in-Hole Task Under Variable Conditions
by: Yasutomi, André Yuji, et al.
Published: (2023)
by: Yasutomi, André Yuji, et al.
Published: (2023)
TaSA: Two-Phased Deep Predictive Learning of Tactile Sensory Attenuation for Improving In-Grasp Manipulation
by: Ponnivalavan, Pranav, et al.
Published: (2026)
by: Ponnivalavan, Pranav, et al.
Published: (2026)
Stereo Multistage Spatial Attention for Real-Time Mobile Manipulation Under Visual Scale Variation and Disturbances
by: Cai, Xianbo, et al.
Published: (2026)
by: Cai, Xianbo, et al.
Published: (2026)
Input-gated Bilateral Teleoperation: An Easy-to-implement Force Feedback Teleoperation Method for Low-cost Hardware
by: Kanai, Yoshiki, et al.
Published: (2025)
by: Kanai, Yoshiki, et al.
Published: (2025)
Focused Blind Switching Manipulation Based on Constrained and Regional Touch States of Multi-Fingered Hand Using Deep Learning
by: Funabashi, Satoshi, et al.
Published: (2025)
by: Funabashi, Satoshi, et al.
Published: (2025)
Continuous Jumping of a Parallel Wire-Driven Monopedal Robot RAMIEL Using Reinforcement Learning
by: Kawaharazuka, Kento, et al.
Published: (2024)
by: Kawaharazuka, Kento, et al.
Published: (2024)
RoboManipBaselines: A Unified Framework for Imitation Learning in Robotic Manipulation across Real and Simulation Environments
by: Murooka, Masaki, et al.
Published: (2025)
by: Murooka, Masaki, et al.
Published: (2025)
LLM-mediated Dynamic Plan Generation with a Multi-Agent Approach
by: Abe, Reo, et al.
Published: (2025)
by: Abe, Reo, et al.
Published: (2025)
A Universal Wire Testing Machine for Enhancing the Performance of Wire-Driven Robots
by: Suzuki, Temma, et al.
Published: (2025)
by: Suzuki, Temma, et al.
Published: (2025)
Deep Predictive Model Learning with Parametric Bias: Handling Modeling Difficulties and Temporal Model Changes
by: Kawaharazuka, Kento, et al.
Published: (2024)
by: Kawaharazuka, Kento, et al.
Published: (2024)
EFGCL: Learning Dynamic Motion through Spotting-Inspired External Force Guided Curriculum Learning
by: Yoneda, Keita, et al.
Published: (2026)
by: Yoneda, Keita, et al.
Published: (2026)
Visual Imitation Learning of Non-Prehensile Manipulation Tasks with Dynamics-Supervised Models
by: Mustafa, Abdullah, et al.
Published: (2024)
by: Mustafa, Abdullah, et al.
Published: (2024)
A Peg-in-hole Task Strategy for Holes in Concrete
by: Yasutomi, André Yuji, et al.
Published: (2024)
by: Yasutomi, André Yuji, et al.
Published: (2024)
Imitation Learning with Additional Constraints on Motion Style using Parametric Bias
by: Kawaharazuka, Kento, et al.
Published: (2024)
by: Kawaharazuka, Kento, et al.
Published: (2024)
Deep Learning-Enhanced Robotic Subretinal Injection with Real-Time Retinal Motion Compensation
by: Wu, Tianle, et al.
Published: (2025)
by: Wu, Tianle, et al.
Published: (2025)
SpaceOctopus: An Octopus-inspired Motion Planning Framework for Multi-arm Space Robot
by: Zhao, Wenbo, et al.
Published: (2024)
by: Zhao, Wenbo, et al.
Published: (2024)
Hybrid Robot Learning for Automatic Robot Motion Planning in Manufacturing
by: Singh, Siddharth, et al.
Published: (2025)
by: Singh, Siddharth, et al.
Published: (2025)
Motion Control in Multi-Rotor Aerial Robots Using Deep Reinforcement Learning
by: Shetty, Gaurav, et al.
Published: (2025)
by: Shetty, Gaurav, et al.
Published: (2025)
Adaptive Robotic Tool-Tip Control Learning Considering Online Changes in Grasping State
by: Kawaharazuka, Kento, et al.
Published: (2024)
by: Kawaharazuka, Kento, et al.
Published: (2024)
Vector Field-Guided Learning Predictive Control for Motion Planning of Mobile Robots with Uncertain Dynamics
by: Lu, Yang, et al.
Published: (2024)
by: Lu, Yang, et al.
Published: (2024)
URPlanner: A Universal Paradigm For Collision-Free Robotic Motion Planning Based on Deep Reinforcement Learning
by: Ying, Fengkang, et al.
Published: (2025)
by: Ying, Fengkang, et al.
Published: (2025)
Motion Planning Diffusion: Learning and Adapting Robot Motion Planning with Diffusion Models
by: Carvalho, J., et al.
Published: (2024)
by: Carvalho, J., et al.
Published: (2024)
Learning Agile Bipedal Motions on a Quadrupedal Robot
by: Li, Yunfei, et al.
Published: (2023)
by: Li, Yunfei, et al.
Published: (2023)
Hybrid Motion Planning with Deep Reinforcement Learning for Mobile Robot Navigation
by: Kolomeytsev, Yury, et al.
Published: (2025)
by: Kolomeytsev, Yury, et al.
Published: (2025)
Learning-based Trajectory Tracking for Bird-inspired Flapping-Wing Robots
by: Cai, Jiaze, et al.
Published: (2024)
by: Cai, Jiaze, et al.
Published: (2024)
KLEIYN : A Quadruped Robot with an Active Waist for Both Locomotion and Wall Climbing
by: Yoneda, Keita, et al.
Published: (2025)
by: Yoneda, Keita, et al.
Published: (2025)
Hardware Design and Learning-Based Software Architecture of Musculoskeletal Wheeled Robot Musashi-W for Real-World Applications
by: Kawaharazuka, Kento, et al.
Published: (2024)
by: Kawaharazuka, Kento, et al.
Published: (2024)
REWW-ARM -- Remote Wire-Driven Mobile Robot: Design, Control, and Experimental Validation
by: Hattori, Takahiro, et al.
Published: (2025)
by: Hattori, Takahiro, et al.
Published: (2025)
Design Optimization of Wire Arrangement with Variable Relay Points in Numerical Simulation for Tendon-driven Robots
by: Kawaharazuka, Kento, et al.
Published: (2024)
by: Kawaharazuka, Kento, et al.
Published: (2024)
Similar Items
-
Sensorimotor Attention and Language-based Regressions in Shared Latent Variables for Integrating Robot Motion Learning and LLM
by: Suzuki, Kanata, et al.
Published: (2024) -
Proprioception Enhances Vision Language Model in Generating Captions and Subtask Segmentations for Robot Task
by: Suzuki, Kanata, et al.
Published: (2025) -
How to Utilize Failure Demo Data?: Effective Data Selection for Imitation Learning Using Distribution Differences in Attention Mechanism
by: Miyamoto, Kana, et al.
Published: (2026) -
Achieving Faster and More Accurate Operation of Deep Predictive Learning
by: Yoshikawa, Masaki, et al.
Published: (2024) -
Compact Task-Aligned Imitation Learning for Laboratory Automation
by: Suzuki, Kanata, et al.
Published: (2026)