scholarly journals QoS Control in Remote Robot Operation with Force Feedback

2021 ◽  
Author(s):  
Pingguo Huang ◽  
Yutaka Ishibashi
Keyword(s):  
Force Feedback ◽  
Industrial Robot ◽  
Force Sensor ◽  
Video Camera ◽  
Haptic Information ◽  
Robot System ◽  
Qos Control ◽  
Stabilization Control ◽  
Robot Systems

Recently, many researchers focus on studies of remote robot operation with force feedback. By using force feedback, since users can touch remote objects and feel the shape, weight, and softness of each object, the efficiency and accuracy of operation can be largely improved. However, when the haptic information such as force and/or position information is transmitted over a QoS (Quality of Service) non-guaranteed network like the Internet, QoE (Quality of Experience) and stability may seriously deteriorate. Therefore, it is important to carry out QoS control and stabilization control together to solve the problems. In this chapter, we mainly focus on QoS control. We also introduce our remote robot system with force feedback which we constructed to study QoS control and stabilization control by experiment. In the system, a user operates a remote industrial robot with a force sensor by using a local haptic interface device while monitoring the robot operation by a video camera. We handle two types of operation; operation with a single remote robot system and that between two remote robot systems. We explain several types of QoS control which we have proposed so far for remote robot operation with force feedback. Finally, we discuss the challenges and future directions of QoS control in remote robot operation with force feedback.

scholarly journals Comparison of Stabilization Control in Cooperation between Remote Robot Systems with Force Feedback

2020 ◽  
pp. 87-92
Author(s):  
Eijiro Taguchi ◽  
Yutaka Ishibashi ◽  
Yuichiro Tateiwa ◽  
Takanori Miyoshi ◽  
Pingguo Huang
Keyword(s):  
Force Feedback ◽  
Stabilization Control ◽  
Robot Systems

scholarly journals Method for the Detection of Tumor Blood Vessels in Neurosurgery Using a Gripping Force Feedback System

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5157
Author(s):  
Hiroki Yokota ◽  
Takeshi Yoneyama ◽  
Tetsuyou Watanabe ◽  
Yasuo Sasagawa ◽  
Mitsutoshi Nakada
Keyword(s):  
Blood Vessel ◽  
Blood Vessels ◽  
Force Feedback ◽  
Correlation Coefficients ◽  
Feedback System ◽  
Force Sensor ◽  
Robot System ◽  
Blood Vessel Detection ◽  
Operating Space ◽  
Gripping Force

Avoiding unnecessary bleeding during neuroendoscopic surgeries is crucial because achieving hemostasis in a narrow operating space is challenging. However, when the location of a blood vessel in a tumor cannot be visually confirmed, unintentional damage to the vessel and subsequent bleeding may occur. This study proposes a method for tumor blood vessel detection using a master–slave surgical robot system equipped with a force sensor in the slave gripper. Using this method, blood pulsation inside a tumor was detected, displayed as a gripping force wave, via the slave force sensor. The characteristics of gripping force due to blood pulsation were extracted by measuring the fluctuation of the force in real time. The presence or absence of blood vessels was determined on the basis of cross-correlation coefficients between the gripping force fluctuation waveform due to blood pulsation and model fluctuation waveform. Experimental validation using two types of simulated tumors (soft: E = 6 kPa; hard: E = 38 kPa) and a simulated blood vessel (E = 1.9 MPa, radius = 0.5 mm, thickness = 0.1 mm) revealed that the presence of blood vessels could be detected while gripping at a constant angle and during transient gripping.

THE CAPABILITY MAP: A TOOL TO ANALYZE ROBOT ARM WORKSPACES

2013 ◽  
Vol 10 (04) ◽  
pp. 1350031 ◽  
Author(s):  
FRANZISKA ZACHARIAS ◽  
CHRISTOPH BORST ◽  
SEBASTIAN WOLF ◽  
GERD HIRZINGER
Keyword(s):  
Industrial Robot ◽  
Humanoid Robots ◽  
Design Phase ◽  
Robot Arm ◽  
Robot System ◽  
Complex Tasks ◽  
Robot Arms ◽  
Cooperative Tasks ◽  
Robot Systems ◽  
The Individual

More and more systems are developed that include several robot arms, like humanoid robots or industrial robot systems. These systems are designed for complex tasks to be solved in cooperation by the robot arms. However, the capabilities of the individual robot arms to perform given tasks or the suitability of a multi-robot system for cooperative tasks cannot be intuitively comprehended. For planning complex tasks or designing robot systems, a representation of a robot arm's workspace is needed that allows to determine from which directions objects in the workspace can be reached. In this paper, the capability map is presented. It is a representation of a robot arm's kinematic capabilities in its workspace. The capability map is used to compare existing robot arms, to support the design phase of an anthropomorphic robot arm and to enable robot workcell planning.

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