A Novel Human-Like Control Framework for Mobile Medical Service Robot

Abstract

Recently, as a highly infectious disease of novel coronavirus (COVID-19) has swept the globe, more and more patients need to be isolated in the rooms of the hospitals, so how to deliver the meals or drugs to these infectious patients is the urgent work. It is a reliable and effective method to transport medical supplies or meals to patients using robots, but how to teach the robot to the destination and to enter the door like a human is an exciting task. In this paper, a novel human-like control framework for the mobile medical service robot is considered, where a Kinect sensor is used to manage human activity recognition to generate a designed teaching trajectory. Meanwhile, the learning technique of dynamic movement primitives (DMP) with the Gaussian mixture model (GMM) is applied to transfer the skill from humans to robots. A neural-based model predictive tracking controller is implemented to follow the teaching trajectory. Finally, some demonstrations are carried out in a hospital room to illustrate the superiority and effectiveness of the developed framework.

Anthropomorphic motion planning for multi-degree-of-freedom arms

“… Takano and Nakamura (2017) proposed a method for extracting motion data information using HMM, which could control the moments of all joints of a humanoid robot to achieve the desired contact force and overall motion. Furthermore, Zhang et al (2020) proposed a new anthropomorphic motion control framework using GMM and DMP to learn the demonstration trajectories and generate the anthropomorphic motion trajectories, which was tested on a mobile service robot to prove its effectiveness.…”

“…With the in-depth study of human movement function, wearable exoskeleton robots ( Liu et al, 2018 ) and medical robots ( Zhang et al, 2020 ) with anthropomorphic motion planning ability have gradually come into view. In the future, it is expected that more products will be introduced to meet human needs.…”

Kinematics and workspace analysis of a robotic arm for medical delivery robots

“…Zhang X et al used a mobile robot platform to deliver food and medicine in a hospital by optimising the robot's path, but with only load-bearing transpositions and no grasping transpositions [2]. Ahmed H. Dallal et al used a WLAN remote controlled mobile robot to carry radioactive materials in an oncology hospital, but the gripping device had few degrees of freedom and was not flexible enough to perform the gripping task in a given positioning position [3].…”

Theory, Applications, and Challenges of Cyber‐Physical Systems 2021

“…Increasing complexities can be due to complex components, for example, some applications of advanced robot manipulators, sensor networks, multiagent systems, humanin-the-loop systems, and also complex environments. In particular, as unstructured environments in manufacturing with multi-spatial and temporal scales, uncertain humanrobot interaction in the complex healthcare system, or intelligent control and multimodal information fusion in largescale complex distributed systems, is the urgent problem to be solved [9][10][11]. ese theoretical, methodological, or practical focus complexities make high-precision and reliable real-time performance difficult to achieve and therefore require the design and development of novel methods for cyber-physical systems [12].…”