Teleoperation of heavy machinery in industry often requires operators to be in close proximity to the plant and issue commands on a per-actuator level using joystick input devices. However, this is non-intuitive and makes achieving desired job properties a challenging task requiring operators to complete extensive and costly training. Despite this, operator fatigue is common with implications for personal safety, project timeliness, cost, and quality. While full automation is not yet achievable due to unpredictability and the dynamic nature of the environment and task, shared control paradigms allow operators to issue high-level commands in an intuitive, task-informed control space while having the robot optimize for achieving desired job properties. In this paper, we compare a number of modes of teleoperation, exploring both the number of dimensions of the control input as well as the most intuitive control spaces. Our experimental evaluations of the performance metrics were based on quantifying the difficulty of tasks based on the well known Fitts' law as well as a measure of how well constraints affecting the task performance were met. Our experiments show that higher performance is achieved when humans submit commands in low-dimensional task spaces as opposed to joint space manipulations.
From the concrete spraying literature, a task space control framework was developed by Honegger and Codourey @cite_18 based on the inverse-kinematics method. The system allows the operator to control the end-effector of the concrete spraying unit using a 6-DoF space mouse. Later work by Girmscheid and Moser @cite_12 developed a sliding autonomy approach for a high-DoF concrete spraying unit. They define three levels of autonomy: (1) A manual mode, consisting of no autonomy and implementing common joint-level control, (2) A semi-automated mode that, using a pre-collected laser scan of a tunnel cavity and computed geometry, allows the operator to command only the position on the wall to spray whilst the system accounts for motion constraints, and (3) An automated mode that plans and executes an entire trajectory. The latter mode, they note, is only in development for tunnel-boring machine projects where the excavated tunnel surface is regular and very smooth. Modes of teleoperation compared in this work are inspired by these control techniques developed for concrete spraying applications.
@cite_18 @cite_12
2103435288 2023197039
In tunneling and mining construction work, heavy and large manipulators are used to spray liquid concrete on the walls. These manipulators are usually operated manually with simple units allowing control of all actuators independently. In cooperation between industry and university, a novel control system has been developed for the redundant heavy manipulator Robojet(R) that supports the operator by calculating the inverse kinematic model and controlling all actuators automatically. The paper presents the solution of the redundant inverse kinematics of the Robojet using the null-space method and its implementation in a control system. Optimized shotcrete application techniques are required in particular tunneling projects. Today, any spraying can be done by hand or by manipulator. With the development in the material technologies, the range of possible operation was enlarged. With automation of the application, an important contribution to improve performance and quality and to reduce rebound may be achieved. At the Swiss Federal Institute of Technology, Zurich, systematic research is done to develop the fully automated process control, focusing on the wet shotcrete method. With the development of the fully automated shotcrete robot, the user will have a very effective tool at his or her disposal to spray concrete shells (fully automated). With the new robot, the user may choose from three different modes: manual, semiautomated, and fully automated spraying. Especially the fully automated mode facilitates higher performance with less danger to the worker's health. Quality control is inherent in the application process in regard to layer thickness, compaction, and homogeneity. We present the development of a full-scale “parallel autonomy” research platform including software and hardware. In the parallel autonomy paradigm, the control of the vehicle is shared; the human is still in control of the vehicle, but the autonomy system is always running in the background to prevent accidents. Our holistic approach includes: (1) a drive-by-wire conversion method only based on reverse engineering mounting of relatively inexpensive sensors onto the vehicle implementation of a localization and mapping system, (4) obstacle detection and (5) a shared controller as well as (6) integration with an advanced autonomy simulation system (Drake) for rapid development and testing. The system can operate in three modes: (a) manual driving, (b) full autonomy, where the system is in complete control of the vehicle and (c) parallel autonomy, where the shared controller is implemented. We present results from extensive testing of a full-scale vehicle on closed tracks that demonstrate these capabilities. This paper describes a strawberry-harvesting robot, a packing robot, and a movable bench system. The harvesting and packing operations in strawberry production require harder, more time-consuming work compared to other operations such as transplanting and chemical spraying, making automation of these tasks desirable. Since harvesting and packing operation account for half of total working hours, automation of these tasks are strongly desired. First of all, based on the findings of many studies on strawberry-harvesting robots for soil culture and elevated substrate culture, our institute of the Bio-oriented Technology Research Advancement Institution and Shibuya Seiki developed a commercial model of a strawberry-harvesting robot, which is chiefly composed a cylindrical manipulator, machine vision, an end-effector, and traveling platform. The results showed an average 54.9 harvesting success rate, 8.6 s cycle time of picking operation, and 102.5 m h work efficiency in hanging-type growing beds in an experimental greenhouse. Secondly, a prototype automatic packing robot consisting of a supply unit and a packing unit was developed. The supply unit picks up strawberries from a harvesting container, and the packing unit sucks each fruit from calyx side and locates its orientation into a tray. Performance testing showed that automatic packing had a task success rate of 97.3 , with a process time per fruit of 7.3 s. Thirdly, a movable bench system was developed, which makes planting beds rotate in longitudinal and lateral ways. This system brought high density production and labour saving operation at a fixed position, such as crop maintenance and harvesting. By setting up the main body of a strawberry-harvesting robot on working space, unmanned operation technique was developed and tested in an experimental greenhouse. Field experiments of these new automation technologies were conducted and gave a potential of practical use.