Dataset Information

Development of a Virtual Force Sensor for a Low-Cost Collaborative Robot and Applications to Safety Control.

ABSTRACT: To protect operators and conform to safety standards for human-machine interactions, the design of collaborative robot arms often incorporates flexible mechanisms and force sensors to detect and absorb external impact forces. However, this approach increases production costs, making the introduction of such robot arms into low-cost service applications difficult. This study proposes a low-cost, sensorless rigid robot arm design that employs a virtual force sensor and stiffness control to enable the safety collision detection and low-precision force control of robot arms. In this design, when a robot arm is subjected to an external force while in motion, the contact force observer estimates the external torques on each joint according to the motor electric current and calculation errors of the system model, which are then used to estimate the external contact force exerted on the robot arm's end-effector. Additionally, a torque saturation limiter is added to the servo drive for each axis to enable the real-time adjustment of joint torque output according to the estimated external force, regulation of system stiffness, and achievement of impedance control that can be applied in safety measures and force control. The design this study developed is a departure from the conventional multisensor flexible mechanism approach. Moreover, it is a low-cost and sensorless design that relies on model-based control for stiffness regulation, thereby improving the safety and force control in robot arm applications.

SUBMITTER: Yen SH

PROVIDER: S-EPMC6612363 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development of a Virtual Force Sensor for a Low-Cost Collaborative Robot and Applications to Safety Control.

Yen Shih-Hsiang SH Tang Pei-Chong PC Lin Yuan-Chiu YC Lin Chyi-Yeu CY

Sensors (Basel, Switzerland) 20190607 11

To protect operators and conform to safety standards for human-machine interactions, the design of collaborative robot arms often incorporates flexible mechanisms and force sensors to detect and absorb external impact forces. However, this approach increases production costs, making the introduction of such robot arms into low-cost service applications difficult. This study proposes a low-cost, sensorless rigid robot arm design that employs a virtual force sensor and stiffness control to enable ...[more]

PMID: 31181701

Similar Datasets

Project description:This article provides a perspective on estimation and control problems in cyberphysical human systems (CPHSs) that work at the intersection of cyberphysical systems and human systems. The article also discusses solutions to some of the problems in CPHSs. One example of a CPHS is a close-proximity human-robot collaboration (HRC) in a manufacturing setting. The issue of the joint operation's efficiency and human factors, such as safety, attention, mental states, and comfort, naturally arise in the HRC context. By considering human factors, robots' actions can be controlled to achieve objectives, including safe operations and human comfort. Alternately, questions arise when robot factors are considered. For example, can we provide direct inputs and information to humans about an environment and the robots in the area such that the objectives of safety, efficiency, and comfort can be satisfied by considering the robots' current capabilities? The article discusses specific problems involved in HRC related to controlling a robot's motion by taking the current actions of the human in the loop with the robot's control system. To this end, two main challenges are discussed: 1) inferring the intention behind human actions by analyzing a person's motion as observed through skeletal tracking and gaze data and 2) a controller design that keeps robot motion constrained to a boundary in a 3D space by using control barrier functions. The intention inference method fuses skeleton-joint tracking data obtained using the Microsoft Kinect sensor and human gaze data gathered from red-green-blue Kinect images. The direction of a human's hand-reaching motion and a goal-reaching point is estimated while performing a joint pick-and-place task. The trajectory of the hand is estimated forward in time based on the gaze and hand motion data at the current time instance. A barrier function method is applied to generate safe robot trajectories along with forecast hand movements to complete the collaborative displacement of an object by a person and a robot. An adaptive controller is then used to track the reference trajectories using the Baxter robot, which is tested in a Gazebo simulation environment.

Dataset Information

Development of a Virtual Force Sensor for a Low-Cost Collaborative Robot and Applications to Safety Control.

Publications

Development of a Virtual Force Sensor for a Low-Cost Collaborative Robot and Applications to Safety Control.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets