Semi-autonomous unmanned aerial manipulator teleoperation for push-and-slide inspection using parallel force/vision control

Performing inspection and maintenance tasks with aerial robots in complex industrial facilities require high levels of maneuverability and dexterity. As full autonomy still struggles to provide robust solutions due to limited adaptability and high development costs, this study explores the paradigm shift towards shared control teleoperation for tilting unmanned aerial manipulators (UAMs). The research initially focuses on integrating onboard camera measurements and interaction force feedback within a parallel force/vision controller for push-and-slide inspection tasks. The control loop lends itself to the development of a semi-autonomous operation architecture that enables a human operator to easily accomplish the task by means of a simple input device. The paper presents a user study evaluating task completion performance with human-in-the-loop control versus fully autonomous execution. Statistical analysis of 20 user experiences provides insights into the levels of autonomy necessary for effective task completion. Among the analyzed control modalities, statistically significant differences arise when the sliding feature is autonomous, denoting it as the most difficult to manually accomplish. The investigation is conducted within a simulated environment to ensure the safety of sensitive instruments and accommodate users with varying levels of expertise. By proposing shared control architectures, this research addresses the challenges of autonomous UAM operations in hazardous industrial environments, highlighting the benefits of human oversight and control in enhancing task efficiency and safety

Shared-Control Teleoperation Methods for a Cable-Suspended Dual-Arm Unmanned Aerial Manipulator

This paper introduces two shared-control teleoperation methods for remotely executing long-reach tasks with a cable-suspended dual-arm unmanned aerial manipulator. The proposed techniques aim to improve task performance and user experience during remote tasks involving interaction with the environment. Two application scenarios are envisioned: pushing against a flat surface to emulate in-contact inspection tasks of infrastructures, and object grasping to simulate debris removal in cluttered environments. The effectiveness of the two shared-control teleoperation methods is evaluated through a human-subjects study involving 10 participants commanding the simulated robot via a joystick interface. Statistical analysis demonstrates significant enhancements in task performance and system usability when using the proposed methods compared to standard teleoperation

Non-Prehensile Object Transportation via Model Predictive Non-Sliding Manipulation Control

This article proposes a model predictive non-sliding manipulation (MPNSM) control approach to safely transport an object on a tray-like end-effector of a robotic manipulator. For the considered non-prehensile transportation task to succeed, both non-sliding manipulation and the robotic system constraints must always be satisfied. To tackle this problem, we devise a model predictive controller enforcing sticking contacts, i.e., preventing sliding between the object and the tray, and assuring that physical limits such as extreme joint positions, velocities, and input torques are never exceeded. The combined dynamic model of the physical system, comprising the manipulator and the object in contact, is derived in a compact form. The associated non-sliding manipulation constraint is formulated such that the parametrized contact forces belong to a conservatively approximated friction cone space. This constraint is enforced by the proposed MPNSM controller, formulated as an optimal control problem that optimizes the objective of tracking the desired trajectory while always satisfying both manipulation and robotic system constraints. We validate our approach by showing extensive dynamic simulations using a torque-controlled 7-degree-of-freedom (DoF) KUKA LBR IIWA robotic manipulator. Finally, demonstrative results from real experiments conducted on a 21-DoF humanoid robotic platform are shown

A Shared-Control Teleoperation Architecture for Nonprehensile Object Transportation

This article proposes a shared-control teleoperation architecture for robot manipulators transporting an object on a tray. Differently from many existing studies about remotely operated robots with firm grasping capabilities, we consider the case in which, in principle, the object can break its contact with the robot end-effector. The proposed shared-control approach automatically regulates the remote robot motion commanded by the user and the end-effector orientation to prevent the object from sliding over the tray. Furthermore, the human operator is provided with haptic cues informing about the discrepancy between the commanded and executed robot motion, which assist the operator throughout the task execution. We carried out trajectory tracking experiments employing an autonomous 7-degree-of-freedom (DoF) manipulator and compared the results obtained using the proposed approach with two different control schemes (i.e., constant tray orientation and no motion adjustment). We also carried out a human-subjects study involving 18 participants in which a 3-DoF haptic device was used to teleoperate the robot linear motion and display haptic cues to the operator. In all experiments, the results clearly show that our control approach outperforms the other solutions in terms of sliding prevention, robustness, commands tracking, and user’s preference