Recognition of Grasping Motion Based on Modal Space Haptic Information Using DP Pattern-Matching Algorithm

The objective of this study is reproduction of physical human actions. The information concerning the human actions are extracted by bilateral teleoperation systems using wearable tendon-driven robots. In the bilateral teleoperation systems, modal transformation is applied to achieve three control goals: position tracking, force feedback, and tension control. The extracted information is provided to the slave robot. To attain the reproduction, a force control scheme is employed. The utility of the proposed method is experimentally verified by applying to a removal operation of a nut.

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“…This paper adopts acceleration-based bilateral controller to achieve haptic transmission [20]- [22].…”

Section: Controller Designmentioning

confidence: 99%

Extraction and realization of human actions

Nozaki

Tanida

Mizoguchi

et al. 2014

2014 IEEE 13th International Workshop on Advanced Motion Control (AMC)

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“…When a robot performs work in an unstructured, dynamic, and populated environment, finding a way to work safely and efficiently becomes more challenging [5]. Safe and efficient human-robot interaction is indispensable to future robotics applications, where humans and robots must collaborate to perform tasks jointly [6].…”

Section: Introductionmentioning

confidence: 99%

Active Collision Avoidance for Human-Manipulator Safety

Liang

Yao

et al. 2022

IEEE Access

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This paper proposes a novel method for active collision avoidance to protect the human who enters a robot's workspace in a human-robot collaborative environment. The proposed method uses a somatosensory sensor to monitor the robot's workspace and detect anyone attempting to enter it. When someone enters the workspace, a Kinect detects and calculates the position of his or her skeleton points in real-time. However, due to the measurement errors and noise of the device, the tracking error increases over time. Therefore, the proposed method applies an improved particle filter (IPF) to accurately estimate the position of the skeleton points. In order to detect the human-robot collision in real-time, the proposed method uses cylinders to establish the bounding box model for human bones and robots and the human-robot collision is replaced by the collision between the cylinders, greatly improving the efficiency of collision detection. Moreover, taking human safety and productivity into account, the robot velocity control is carried out based on the distance between the robot and human. Then, the proposed method uses a rule-based logic system to analyze human motion so that the robot can take appropriate measures to avoid humans. Finally, the dynamic roadmap (DRM) approach plans new paths in real-time to allow robots to bypass humans. By actively avoiding collisions, the proposed method ensures that the robot will never touch the human body. The significant advantage of the proposed method is that it can detect humans in real-time, analyze their behavior and protect humans without any modification to the robot. The proposed method has been tested in practical applications, and the results show that it can successfully guarantee the safety of people entering the robot's workspace.

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“…R OBOTIC teleoperation systems with haptic feedback have attracted a lot of attention [1]- [3]. Utilization of teleoperation systems are highly demanded to perform various tasks under such as viral environments, sterile environments, radioactive environments, space, high places, burning/frigid environments where it is undesirable for humans to enter.…”

Section: Introductionmentioning

confidence: 99%