Robotic Intelligence and Automation

Research on small sample target detection for underwater robot

Hu Luo, Haobin Ruan, Dawei Tu

The purpose of this paper is to propose a whole set of methods for underwater target detection, because most underwater objects have small samples, low quality underwater images…

Bioinspired sensors and applications in intelligent robots: a review

Yanmin Zhou, Zheng Yan, Ye Yang, Zhipeng Wang, Ping Lu, Philip F. Yuan, Bin He

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing…

A memory and attention-based reinforcement learning for musculoskeletal robots with prior knowledge of muscle synergies

Xiaona Wang, Jiahao Chen, Hong Qiao

Limited by the types of sensors, the state information available for musculoskeletal robots with highly redundant, nonlinear muscles is often incomplete, which makes the control…

Research on decoupling control of single leg joints of hydraulic quadruped robot

Bingwei Gao, Hongjian Zhao, Wenlong Han, Shilong Xue

This study proposes a predictive neural network model reference decoupling control method for the coupling problem between the leg joints of hydraulic quadruped robots, and…

Non-rigid point set registration based on Gaussian mixture model with integrated feature divergence

Chuyu Tang, Hao Wang, Genliang Chen, Shaoqiu Xu

This paper aims to propose a robust method for non-rigid point set registration, using the Gaussian mixture model and accommodating non-rigid transformations. The posterior…

Adaptive positioning method for ball head based on impedance control

Yang Liu, Xiang Huang, Shuanggao Li, Wenmin Chu

Component positioning is an important part of aircraft assembly, aiming at the problem that it is difficult to accurately fall into the corresponding ball socket for the ball head…

Robot skill learning and the data dilemma it faces: a systematic review

Rong Jiang, Bin He, Zhipeng Wang, Xu Cheng, Hongrui Sang, Yanmin Zhou

Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show…