학술논문

A Self-Tuning Impedance-Based Interaction Planner for Robotic Haptic Exploration
Document Type
Periodical
Source
IEEE Robotics and Automation Letters IEEE Robot. Autom. Lett. Robotics and Automation Letters, IEEE. 7(4):9461-9468 Oct, 2022
Subject
Robotics and Control Systems
Computing and Processing
Components, Circuits, Devices and Systems
Robots
Impedance
Trajectory
Planning
Task analysis
Robot sensing systems
Uncertainty
Compliance and impedance control
integrated planning and control
planning under uncertainty
Language
ISSN
2377-3766
2377-3774
Abstract
This letter presents a novel interaction planning method that exploits impedance tuning techniques in response to environmental uncertainties and unpredictable conditions using haptic information only. The proposed algorithm plans the robot's trajectory based on the haptic interaction with the environment and adapts planning strategies as needed. Two approaches are considered: Exploration and Bouncing strategies. The Exploration strategy takes the actual motion of the robot into account in planning, while the Bouncing strategy exploits the forces and the motion vector of the robot. Moreover, self-tuning impedance is performed according to the planned trajectory to ensure compliant contact and low contact forces. In order to show the performance of the proposed methodology, two experiments with a torque-controller robotic arm are carried out. The first considers a maze exploration without obstacles, whereas the second includes obstacles. The proposed method performance is analyzed and compared against previously proposed solutions in both cases. Experimental results demonstrate that: i) the robot can successfully plan its trajectory autonomously in the most feasible direction according to the interaction with the environment, and ii) a compliant interaction with an unknown environment despite the uncertainties is achieved. Finally, a scalability demonstration is carried out to show the potential of the proposed method under multiple scenarios.