ABOUT SARA

The WRC Symposium on Advanced Robotics and Automation (WRC SARA) is scheduled to be held in Beijing on August 21, 2026 during 2026 World Robot Conference (WRC). It is an international symposium focusing on all areas related to roboticsand automation. Over its precious seven sessions since 2018, all accepted and presented papers have been included in lEEE Xplore and El indexed.

HIGHLIGHTS OF WRC SARA 2025

AWARD WINNERS

Best Conference Paper Award

Best Student Paper Award

Phase surface electromyography (sEMG) based muscle onset detection

Wenbo Yuan
Changqiu Zhou
Yafei Zhao
Ziqin Ling
Jiangcheng Chen
Ning Xi

Surgical Phase Detection with Deep Learning for Thoracoscopic pulmonary Lobectomy Surgery

Qian Yang
Chang Liu
Zhuojia Zhou
Yongqiang Feng
Heng Zheng
Jie Tang
Bai-Quan Su

Ultra-sensitive Aorta Pressure Sensor Based on Graphene

Jing Zhao
Yiqi Yin
Zhongyi Li
Zhejian Feng
Xueer Zeng

PRESENTATION VIDEOS

Enhancing the Adaptability of Hexapod Robots Via Multi-Agent Reinforcement Learning and Value Function Decomposition
Deep Reinforcement Learning-Based Path Planning with Dynamic Collision Probability for Mobile Robot
Continuous Motion Planning for Mobile Robots Using Fuzzy Deep Reinforcement Learning
An Optimized Variational Bayesian Point Set Matching Approach Using Coordinate Ascent and Simulated Annealing
Optimal Viewpoints Selection for Monitoring Teleoperators Based on Event Artificial Potential Method
Humanoid Grasping with Multi-Finger Dexterous Hands Based on DM-KMP
Bayesian Optimization Based D-S Fusion for Brain-Robot Cooperation to Navigate a Mobile Robot
A Pain Assessment Method Based on Decoding Local Field Potential Signals

ABOUT SARA

HIGHLIGHTS OF WRC SARA 2025

AWARD WINNERS

Phase surface electromyography (sEMG) based muscle onset detection

Surgical Phase Detection with Deep Learning for Thoracoscopic pulmonary Lobectomy Surgery

Ultra-sensitive Aorta Pressure Sensor Based on Graphene

PRESENTATION VIDEOS

Enhancing the Adaptability of Hexapod Robots Via Multi-Agent Reinforcement Learning and Value Function Decomposition

Deep Reinforcement Learning-Based Path Planning with Dynamic Collision Probability for Mobile Robot

Continuous Motion Planning for Mobile Robots Using Fuzzy Deep Reinforcement Learning

An Optimized Variational Bayesian Point Set Matching Approach Using Coordinate Ascent and Simulated Annealing

Optimal Viewpoints Selection for Monitoring Teleoperators Based on Event Artificial Potential Method

Humanoid Grasping with Multi-Finger Dexterous Hands Based on DM-KMP

Bayesian Optimization Based D-S Fusion for Brain-Robot Cooperation to Navigate a Mobile Robot

A Pain Assessment Method Based on Decoding Local Field Potential Signals