This letter presents an inverse kinematics approach that combines two well-known Jacobian based methods, the task-priority framework and an optimization-based approach, such that tracking and optimization tasks can be executed simultaneously. The novelty of the proposed algorithm lies in the ability to smoothly switch between different tasks and thus to allow for a seamless and safe transition during robot operation. This has shown to improve the efficiency and user experience, especially during tele-operated interventions in complex environments.

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This paper presents a method for semiautonomous teleimpedance where the control is shared between the human operator and the robot. The human commands the position of the teleoperated robotic arm end-effector while the robot autonomously adjusts the impedance depending on the object with which the end-effector interacts. We developed a vision system that calculates the appropriate robot stiffness based on the detected object geometry and material and object’s relation to the environment. This system uses an RGB-D camera near the robot’s end-effector to capture different perspectives of the scene. To validate the proposed method, we conducted experiments on a teleoperation system where a Force Dimension Sigma7 haptic device was used to operate a KUKA LBR iiwa robotics arm. At the same time, the Intel RealSense D455 depth camera provided the visual input. We examined two practical tasks: engaging with bolts on a plate and polishing a stripe.@en

Teleoperation is a crucial technology enabling human operators to control robots remotely to perform tasks in hazardous and difficult-to-access environments. Tasks in such environments often involve complex physical interactions with tools and objects of various softness. To this end, teleimpedance enables the operators to adjust the robot impedance in real-time to simplify such interactions. While the existing teleimpedance approaches provide several interfaces to command the robot impedance, there are no interfaces to visualize both the commanded impedance and that of the objects to be interacted with. This paper presents a novel interface to provide visual feedback on the impedance of remote robots and objects. To do so, we use virtual stiffness ellipsoids and different modes that display the individual impedance of the robot and objects as well as combined post-contact impedance. The key advantage of visual feedback on the impedance compared to force feedback is that the operator can see the interaction characteristics before the contact occurs. This enables the operator to act proactively before contact rather than just reactively after the contact. This paper also proposes a new intuitive way to command the robot impedance using mixed reality, interacting with these ellipsoids and modifying them as needed. To demonstrate the key functionalities of the developed interface, we performed proof-of-concept experiments on teleoperated tasks.@en

At CERN, radiation surveys of equipment and beam lines are important for safety and analysis throughout the accelerator complex. Radiation measurements are highly dependent on the distance between the sensor and the radiation source. If this distance can be accurately established, the measurements can be used to better understand the radiation levels of the components and can be used for calibration purposes. When surveys are undertaken by the Train Inspection Monorail (TIM) robot, the sensor is at a constant distance from the rail, which means that it is at a known distance and height from the centre of the beam line. However, the distance of the sensor to the closest surface of the beam line varies according to what kind of equipment is installed on the beam line at this point. Ideally, a robotic survey would be completed with online adaption of the sensor position according to the equipment present in the LHC. This new approach establishes a scan of the surface with a 2D LiDAR while moving along the tunnel axis in order to obtain a 3D scan of the environment. This 3D scan will be used to generate online trajectories that will allow the robot to accurately follow the beam line and thus measure the radiation levels.

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