Safety in a Human Robot Interactive: Application to Haptic Perception

Guda, Vamsi; Chablat, Damien; Chevallereau, Christine

doi:10.1007/978-3-030-49695-1_38

Cited by 7 publications

(7 citation statements)

References 16 publications

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“…The placement of the robot in the scene was chosen to reach all the places where the user's hand would interact with the robot's probe. A detailed explanation of the user and robot placement is given in [40]. The user wore an HMD, and Vive trackers were attached to the user's hands as shown in Fig.…”

Section: A Experimental Setupmentioning

confidence: 99%

Motion Prediction With Gaussian Processes for Safe Human–Robot Interaction in Virtual Environments

Mugisha,

Krishna Guda,

Chevallereau

et al. 2024

IEEE Access

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Humans use collaborative robots as tools for accomplishing various tasks. The interaction between humans and robots happens in tight shared workspaces. However, these machines must be safe to operate alongside humans to minimize the risk of accidental collisions. Ensuring safety imposes many constraints, such as reduced torque and velocity limits during operation, thus increasing the time to accomplish many tasks. However, for applications such as using collaborative robots as haptic interfaces with intermittent contacts for virtual reality applications, speed limitations result in poor user experiences. This research aims to improve the efficiency of a collaborative robot while improving the safety of the human user. We used Gaussian process models to predict human hand motion and developed strategies for human intention detection based on hand motion and gaze to improve the time for the robot and human security in a virtual environment. We then studied the effect of prediction. Results from comparisons show that the prediction models improved the robot time by 3% and safety by 17%. When used alongside gaze, prediction with Gaussian process models resulted in an improvement of the robot time by 2% and the safety by 13%.

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Section: A Experimental Setupmentioning

confidence: 99%

Motion Prediction With Gaussian Processes for Safe Human–Robot Interaction in Virtual Environments

Mugisha,

Krishna Guda,

Chevallereau

et al. 2024

IEEE Access

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“…Studies in [2] [3] have focused on the perception of stiffness, friction, and shape of tangible objects in VR using a wearable 2-DoF (degrees of freedom) tactical device on a finger to alter the user's sense of touch. In [4,5], a 6-DoF cobot is used in a VR environment to simulate the interior of a car, where interaction between the robot and the user is expected just at specific, instantaneous points. This proposal is to use ICIs (Intermittent Contact Interfaces) [6] to minimise the amount of human-robot interactions to increase safety.…”

Section: Intermittent Contact Interfacementioning

confidence: 99%

“…The laboratory setup consists of a UR5 robotic system and a car chair in a face-to-face configuration (Figure 2). The location and height of the robot was determined by [4] to be 75 cm above the floor. This position is optimal enough for the robot to reach all the interaction points that the system is interested in reaching.…”

Section: Laboratory Setupmentioning

confidence: 99%

“…These three elements are the ones that the trajectory planning algorithms must consider in order for them to avoid any collision state existing with one of these elements. The robot support was modelled to match the size of the real system that was optimally defined [4]. For the configuration of the plannig group, MoveIt has an integrated graphical interface to create all the configuration files related to the kinematics, controllers, Semantic Robot Description Format (SRDF) and other files for the usage of the robot in ROS.…”

Section: Planning Groupmentioning

confidence: 99%

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Trajectory planning in Dynamics Environment : Application for Haptic Perception in Safe HumanRobot Interaction

Gutierrez,

Guda,

Mugisha

et al. 2022

Preprint

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In a human-robot interaction system, the most important thing to consider is the safety of the user. This must be guaranteed in order to implement a reliable system. The main objective of this paper is to generate a safe motion scheme that takes into account the obstacles present in a virtual reality (VR) environment. The work is developed using the MoveIt software in ROS to control an industrial robot UR5. Thanks to this, we will be able to set up the planning group, which is realised by the UR5 robot with a 6-sided prop and the base of the manipulator, in order to plan feasible trajectories that it will be able to execute in the environment. The latter is based on the interior of a vehicle, containing a user (which would be the user in this case) for which the configuration will also be made to be taken into account in the system. To do this, we first investigated the software's capabilities and options for path planning, as well as the different ways to execute the movements. We also compared the different trajectory planning algorithms that the software is capable of using in order to determine which one is best suited for the task. Finally, we proposed different mobility schemes to be executed by the robot depending on the situation it is facing. The first one is used when the robot has to plan trajectories in a safe space, where the only obstacle to avoid is the user's workspace. The second one is used when the robot has to interact with the user, where a mannequin model represents the user's position as a function of time, which is the one to be avoided.

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“…The robot is fixed on a 75 cm high table and the user sits on a seat 60 cm above the floor. The placement of the robot in the scene has been chosen to be able to reach all the places where the user's hand will want to have haptic interaction with the robot's probe [9].…”

Section: Description Of the Contextmentioning

confidence: 99%

Safe Collaboration Between Human and Robot in a Context of Intermittent Haptique Interface

Mugisha

Zoppi

Molfino

et al. 2021

Volume 8B: 45th Mechanisms and Robotics Conference (MR)

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In the list of interfaces used to make virtual reality, haptic interfaces allow users to touch a virtual world with their hands. Traditionally, the user’s hand touches the end effector of a robotic arm. When there is no contact, the robotic arm is passive; when there is contact, the arm suppresses mobility to the user’s hand in certain directions. Unfortunately, the passive mode is never completely seamless to the user. Haptic interfaces with intermittent contacts are interfaces using industrial robots that move towards the user when contact needs to be made. As the user is immersed via a virtual reality Head Mounted Display (HMD), he cannot perceive the danger of a collision when he changes his area of interest in the virtual environment. The objective of this article is to describe movement strategies for the robot to be as fast as possible on the contact zone while guaranteeing safety. This work uses the concept of predicting the position of the user through his gaze direction and the position of his dominant hand (the one touching the object). A motion generation algorithm is proposed and then applied to a UR5 robot with an HTC vive tracker system for an industrial application involving the analysis of materials in the interior of a car.

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Safety in a Human Robot Interactive: Application to Haptic Perception

Cited by 7 publications

References 16 publications

Motion Prediction With Gaussian Processes for Safe Human–Robot Interaction in Virtual Environments

Motion Prediction With Gaussian Processes for Safe Human–Robot Interaction in Virtual Environments

Trajectory planning in Dynamics Environment : Application for Haptic Perception in Safe HumanRobot Interaction

Safe Collaboration Between Human and Robot in a Context of Intermittent Haptique Interface

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