Interactive Adaptive Admittance Control of an Assistive Robotic Rollator for Mobility Assistance

Abstract

This diploma thesis deals with the subject of control of a robotic rollator in physical interaction with the human-user. The project focuses on two research directions. The first concerns the design and training of an Admittance model to drive a smart walker with Force/Torque sensors mounted on its handles. In the second direction, a novel intention-based navigation Controller is proposed that connects the Admittance model with a dynamic local path planner. This shared human-robot control strategy is used to implement an Assistive Mode for driving, while also being extended with an Intention Recognition algorithm for undecidability resolution and a Damping Adaptation technique. The assistance is about guiding the user with safety on dangerous paths, while the undecidability refers to picking the human intented direction of motion on situations where there are multiple possible ways of movement, like in a T-junction. On top of these, the adaptation of the damping coefficient of the Admittance model is proposed, based on the state of the system, to make the human-walker collaboratation more realistic and useful. To evaluate the proposed methods, various experimental results are presented, some for Free Space and some for Constrained Space. In Free Space the driving of the robot is tested with the estimated Admittance model and with adjusted damping, while in Constrained Space specific case scenarios are considered to show the effectiveness of the implemented navigation Controller, methods, and assistive features.