Intuitive Robot Teleoperation through Multi-Sensor Informed Mixed Reality Visual Aids

© 2021 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.Mobile robotic systems have evolved to include sensors capable of truthfully describing robot status and operating environment as accurately and reliably as never before. This possibility is challenged by effective sensor data exploitation, because of the cognitive load an operator is exposed to, due to the large amount of data and time-dependency constraints. This paper addresses this challenge in remote-vehicle teleoperation by proposing an intuitive way to present sensor data to users by means of using mixed reality and visual aids within the user interface. We propose a method for organizing information presentation and a set of visual aids to facilitate visual communication of data in teleoperation control panels. The resulting sensor-information presentation appears coherent and intuitive, making it easier for an operator to catch and comprehend information meaning. This increases situational awareness and speeds up decision-making. Our method is implemented on a real mobile robotic system operating outdoor equipped with on-board internal and external sensors, GPS, and a reconstructed 3D graphical model provided by an assistant drone. Experimentation verified feasibility while intuitive and comprehensive visual communication was confirmed through a qualitative assessment, which encourages further developments.Peer reviewe

Recent Advancements in Augmented Reality for Robotic Applications: A Survey

Robots are expanding from industrial applications to daily life, in areas such as medical robotics, rehabilitative robotics, social robotics, and mobile/aerial robotics systems. In recent years, augmented reality (AR) has been integrated into many robotic applications, including medical, industrial, human–robot interactions, and collaboration scenarios. In this work, AR for both medical and industrial robot applications is reviewed and summarized. For medical robot applications, we investigated the integration of AR in (1) preoperative and surgical task planning; (2) image-guided robotic surgery; (3) surgical training and simulation; and (4) telesurgery. AR for industrial scenarios is reviewed in (1) human–robot interactions and collaborations; (2) path planning and task allocation; (3) training and simulation; and (4) teleoperation control/assistance. In addition, the limitations and challenges are discussed. Overall, this article serves as a valuable resource for working in the field of AR and robotic research, offering insights into the recent state of the art and prospects for improvement

Sensor Augmented Virtual Reality Based Teleoperation Using Mixed Autonomy

A multimodal teleoperation interface is introduced, featuring an integrated virtual reality (VR) based simulation augmented by sensors and image processing capabilities onboard the remotely operated vehicle. The proposed virtual reality interface fuses an existing VR model with live video feed and prediction states, thereby creating a multimodal control interface. VR addresses the typical limitations of video based teleoperation caused by signal lag and limited field of view, allowing the operator to navigate in a continuous fashion. The vehicle incorporates an onboard computer and a stereo vision system to facilitate obstacle detection. A vehicle adaptation system with a priori risk maps and a real-state tracking system enable temporary autonomous operation of the vehicle for local navigation around obstacles and automatic re-establishment of the vehicle’s teleoperated state. The system provides real time update of the virtual environment based on anomalies encountered by the vehicle. The VR based multimodal teleoperation interface is expected to be more adaptable and intuitive when compared with other interfaces

Exploring Robot Teleoperation in Virtual Reality

This thesis presents research on VR-based robot teleoperation with a focus on remote environment visualisation in virtual reality, the effects of remote environment reconstruction scale in virtual reality on the human-operator's ability to control the robot and human-operator's visual attention patterns when teleoperating a robot from virtual reality. A VR-based robot teleoperation framework was developed, it is compatible with various robotic systems and cameras, allowing for teleoperation and supervised control with any ROS-compatible robot and visualisation of the environment through any ROS-compatible RGB and RGBD cameras. The framework includes mapping, segmentation, tactile exploration, and non-physically demanding VR interface navigation and controls through any Unity-compatible VR headset and controllers or haptic devices. Point clouds are a common way to visualise remote environments in 3D, but they often have distortions and occlusions, making it difficult to accurately represent objects' textures. This can lead to poor decision-making during teleoperation if objects are inaccurately represented in the VR reconstruction. A study using an end-effector-mounted RGBD camera with OctoMap mapping of the remote environment was conducted to explore the remote environment with fewer point cloud distortions and occlusions while using a relatively small bandwidth. Additionally, a tactile exploration study proposed a novel method for visually presenting information about objects' materials in the VR interface, to improve the operator's decision-making and address the challenges of point cloud visualisation. Two studies have been conducted to understand the effect of virtual world dynamic scaling on teleoperation flow. The first study investigated the use of rate mode control with constant and variable mapping of the operator's joystick position to the speed (rate) of the robot's end-effector, depending on the virtual world scale. The results showed that variable mapping allowed participants to teleoperate the robot more effectively but at the cost of increased perceived workload. The second study compared how operators used a virtual world scale in supervised control, comparing the virtual world scale of participants at the beginning and end of a 3-day experiment. The results showed that as operators got better at the task they as a group used a different virtual world scale, and participants' prior video gaming experience also affected the virtual world scale chosen by operators. Similarly, the human-operator's visual attention study has investigated how their visual attention changes as they become better at teleoperating a robot using the framework. The results revealed the most important objects in the VR reconstructed remote environment as indicated by operators' visual attention patterns as well as their visual priorities shifts as they got better at teleoperating the robot. The study also demonstrated that operators’ prior video gaming experience affects their ability to teleoperate the robot and their visual attention behaviours