Search Results for author: Ze Ji

Found 7 papers, 3 papers with code

CasIL: Cognizing and Imitating Skills via a Dual Cognition-Action Architecture

no code implementations28 Sep 2023 Zixuan Chen, Ze Ji, Shuyang Liu, Jing Huo, Yiyu Chen, Yang Gao

Heuristically, we extend the usual notion of action to a dual Cognition (high-level)-Action (low-level) architecture by introducing intuitive human cognitive priors, and propose a novel skill IL framework through human-robot interaction, called Cognition-Action-based Skill Imitation Learning (CasIL), for the robotic agent to effectively cognize and imitate the critical skills from raw visual demonstrations.

Imitation Learning

Recent Advances of Deep Robotic Affordance Learning: A Reinforcement Learning Perspective

no code implementations9 Mar 2023 Xintong Yang, Ze Ji, Jing Wu, Yu-Kun Lai

As a popular concept proposed in the field of psychology, affordance has been regarded as one of the important abilities that enable humans to understand and interact with the environment.

reinforcement-learning Reinforcement Learning (RL)

Abstract Demonstrations and Adaptive Exploration for Efficient and Stable Multi-step Sparse Reward Reinforcement Learning

1 code implementation19 Jul 2022 Xintong Yang, Ze Ji, Jing Wu, Yu-Kun Lai

Although Deep Reinforcement Learning (DRL) has been popular in many disciplines including robotics, state-of-the-art DRL algorithms still struggle to learn long-horizon, multi-step and sparse reward tasks, such as stacking several blocks given only a task-completion reward signal.

An Open-Source Multi-Goal Reinforcement Learning Environment for Robotic Manipulation with Pybullet

2 code implementations12 May 2021 Xintong Yang, Ze Ji, Jing Wu, Yu-Kun Lai

This work re-implements the OpenAI Gym multi-goal robotic manipulation environment, originally based on the commercial Mujoco engine, onto the open-source Pybullet engine.

Multi-Goal Reinforcement Learning OpenAI Gym +1

Accelerated Sim-to-Real Deep Reinforcement Learning: Learning Collision Avoidance from Human Player

1 code implementation21 Feb 2021 Hanlin Niu, Ze Ji, Farshad Arvin, Barry Lennox, Hujun Yin, Joaquin Carrasco

An efficient training strategy is proposed to allow a robot to learn from both human experience data and self-exploratory data.

Navigate Reinforcement Learning (RL)

3D Vision-guided Pick-and-Place Using Kuka LBR iiwa Robot

no code implementations21 Feb 2021 Hanlin Niu, Ze Ji, Zihang Zhu, Hujun Yin, Joaquin Carrasco

This paper presents the development of a control system for vision-guided pick-and-place tasks using a robot arm equipped with a 3D camera.

Low-cost Measurement of Industrial Shock Signals via Deep Learning Calibration

no code implementations7 Feb 2019 Houpu Yao, Jingjing Wen, Yi Ren, Bin Wu, Ze Ji

The results show that the proposed network is capable to map low-end shock signals to its high-end counterparts with satisfactory accuracy.

Cannot find the paper you are looking for? You can Submit a new open access paper.