Abstract
In physical Human–Robot Interaction (pHRI), forces exerted by humans need to be estimated to accommodate robot commands to human constraints, preferences, and needs. This paper presents a method for the estimation of the interaction forces between a human and a robot using a gripper with proprioceptive sensing. Specifically, we measure forces exerted by a human limb grabbed by an underactuated gripper in a frontal plane using only the gripper’s own sensors. This is achieved via a regression method, trained with experimental data from the values of the phalanx angles and actuator signals. The proposed method is intended for adaptive shared control in limb manipulation. Although adding force sensors provides better performance, the results obtained are accurate enough for this application. This approach requires no additional hardware: it relies uniquely on the gripper motor feedback—current, position and torque—and joint angles. Also, it is computationally cheap, so processing times are low enough to allow continuous human-adapted pHRI for shared control.
Highlights
Recent trends in robotics pursue the incorporation of robotic systems among people
Force sensing is important in physical Human–Robot Interaction, where robots are expected to physically manipulate a person, e.g., during rehabilitation [7], or when using exoskeletons [8] or prosthesis [9]
We propose two regression methods to obtain L : (i) Support Vector Regression (SVR) [32]; and (ii) Random Forest Regression (RFR) [33]
Summary
Recent trends in robotics pursue the incorporation of robotic systems among people. Social robots are taking on increasing importance, mostly for healthcare applications, i.e., helping patients [1]or elderly people [2]. Force sensing is important in physical Human–Robot Interaction (pHRI), where robots are expected to physically manipulate a person, e.g., during rehabilitation [7], or when using exoskeletons [8] or prosthesis [9]. In these cases, dependability and safety become a major concern [10,11], especially when it is up to the robot to intentionally touch and/or manipulate people using grippers [12]. These applications include assistive robotics [13], search and rescue missions [14]
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