Sensorless Force Estimation Based on Teleoperation Robot State Information

ABSTRACT In robot operation, ensuring the robot can safely contact the target requires accurate contact force information. At present, in most scenarios, robots can accurately measure contact force using force sensors. However, in special environments such as healthcare and nuclear industries, due to the limited installation space for sensors and the harsh working conditions, the use of force sensors faces numerous challenges and is difficult to deploy widely or operate stably. Therefore, this paper proposes a robot end force estimation method without force sensors. This method utilizes the state information of each joint of the robot and establishes the correlation between the contact force and the state information through the Neighbor‐Aware RNN Network we proposed to accurately estimate the contact force at the robot end. This neural network can handle the dynamic temporal characteristics of the information of each joint of the robot, as well as the spatial correlation information of each joint. It learns the relationship between the state information of each joint of the robot and the contact force through an end‐to‐end approach, and ultimately outputs the three‐axis force estimation results. The experimental results show that this method performs exceptionally well in the task of robot contact force estimation, and its various evaluation indicators are significantly superior to those of other force estimation methods.