Zeguo Yang, Mantian Li, Fusheng Zha, Xin Wang, Pengfei Wang and Wei Guo
This paper aims to introduce an imitation learning framework for a wheeled mobile manipulator based on dynamical movement primitives (DMPs). A novel mobile manipulator with the…
Abstract
Purpose
This paper aims to introduce an imitation learning framework for a wheeled mobile manipulator based on dynamical movement primitives (DMPs). A novel mobile manipulator with the capability to learn from demonstration is introduced. Then, this study explains the whole process for a wheeled mobile manipulator to learn a demonstrated task and generalize to new situations. Two visual tracking controllers are designed for recording human demonstrations and monitoring robot operations. The study clarifies how human demonstrations can be learned and generalized to new situations by a wheel mobile manipulator.
Design/methodology/approach
The kinematic model of a mobile manipulator is analyzed. An RGB-D camera is applied to record the demonstration trajectories and observe robot operations. To avoid human demonstration behaviors going out of sight of the camera, a visual tracking controller is designed based on the kinematic model of the mobile manipulator. The demonstration trajectories are then represented by DMPs and learned by the mobile manipulator with corresponding models. Another tracking controller is designed based on the kinematic model of the mobile manipulator to monitor and modify the robot operations.
Findings
To verify the effectiveness of the imitation learning framework, several daily tasks are demonstrated and learned by the mobile manipulator. The results indicate that the presented approach shows good performance for a wheeled mobile manipulator to learn tasks through human demonstrations. The only thing a robot-user needs to do is to provide demonstrations, which highly facilitates the application of mobile manipulators.
Originality/value
The research fulfills the need for a wheeled mobile manipulator to learn tasks via demonstrations instead of manual planning. Similar approaches can be applied to mobile manipulators with different architecture.
Details
Keywords
Wei Guo, Shiyin Qiu, Fusheng Zha, Jing Deng, Xin Wang and Fei Chen
This paper aims to propose a novel balance-assistive control strategy for hip exoskeleton robot.
Abstract
Purpose
This paper aims to propose a novel balance-assistive control strategy for hip exoskeleton robot.
Design/methodology/approach
A hierarchical balance assistive controller based on the virtual stiffness model of extrapolated center of mass (XCoM) is proposed and tested by exoskeleton balance assistive control experiments.
Findings
Experiment results show that the proposed controller can accelerate the swing foot chasing XCoM and enlarge the margin of stability.
Originality/value
As a proof of concept, this paper shows the potential for exoskeleton to actively assist human regain balance in sagittal plane when human suffers from a forward or backward disturbing force.