Human-Walking-Intention-Based Motion Control of an Omnidirectional-Type Cane Robot

TLDR

Recognizing a user’s walking intention is crucial for controlling the cane robot’s motion. The study aims to design an intelligent cane robot that quantitatively captures users’ walking intention via the proposed intentional direction (ITD) concept. The robot, comprising a stick, sensors, and a three‑wheel omnidirectional base, uses state and observation models of ITD derived from walking modes and interaction forces, applies a Kalman filter for online intention inference, and implements an admittance control scheme validated by experiments on flat and sloped terrain. Experiments demonstrate that intention‑based admittance control makes users feel more natural and comfortable.

Abstract

An intelligent cane robot is designed for aiding the elderly and handicapped people's walking. The robot consists of a stick, a group of sensors, and an omnidirectional basis driven by three Swedish wheels. Recognizing the user's walking intention plays an important role in the motion control of our cane robot. To quantitatively describe the user's walking intention, a concept called "intentional direction (ITD)" is proposed. Both the state model and the observation model of ITD are obtained by enumerating the possible walking modes and analyzing the relationship between the human–robot interaction force and the walking intention. From these two models, the user's walking intention can be online inferred using the Kalman filtering technique. Based on the estimated intention, a new admittance motion control scheme is proposed for the cane robot. Walking experiments aided by the cane robot on a flat ground and slope are carried out to validate the proposed control approach. The experimental results show that the user feels more natural and comfortable when our intention-based admittance control is applied.