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Teleoperation enables complex robot platforms to perform tasks beyond the scope of the current state-of-the-art robot autonomy by imparting human intelligence and critical thinking to these operations. For seamless control of robot platforms, it is essential to facilitate optimal situational awareness of the workspace for the operator through active telepresence cameras. However, the control of these active telepresence cameras adds an additional degree of complexity to the task of teleoperation. In this paper we present our results from the user study that investigates: (1) how the teleoperator learns or adapts to performing the tasks via active cameras modeled after camera placements on the TRINA humanoid robot; (2) the perception-action coupling operators implement to control active telepresence cameras, and (3) the camera preferences for performing the tasks. These findings from the human motion analysis and post-study survey will help us determine desired design features for robot teleoperation interfaces and assistive autonomy. 

Robot teleoperation is an emerging field of study with wide applications in exploration, manufacturing, and healthcare, because it allows users to perform complex remote tasks while remaining distanced and safe. Haptic feedback offers an immersive user experience and expands the range of tasks that can be accomplished through teleoperation. In this paper, we present a novel wearable haptic feedback device for a teleoperation system that applies kinesthetic force feedback to the fingers of a user. The proposed device, called a ‘haptic muscle’, is a soft pneumatic actuator constructed from a fabric-silicone composite in a toroidal structure. We explore the requirements of the ideal haptic feedback mechanism, construct several haptic muscles using different materials, and experimentally determine their dynamic pressure response as well as sensitivity (their ability to communicate small changes in haptic feedback). Finally, we integrate the haptic muscles into a data glove and a teleoperation system and perform several user tests. Our results show that most users could detect detect force changes as low as 3% of the working range of the haptic muscles. We also find that the haptic feedback causes users to apply up to 52% less force on an object while handling soft and fragile objects with a teleoperation system. 

Lasers are an essential tool in modern medical practice, and their applications span a wide spectrum of specialties. In laryngeal microsurgery, lasers are frequently used to excise tumors from the vocal folds [1]. Several research groups have recently developed robotic systems for these procedures [2-4], with the goal of providing enhanced laser aiming and cutting precision. Within this area of research, one of the problems that has received considerable attention is the automatic control of the laser focus. Briefly, laser focusing refers to the process of optically adjusting a laser beam so that it is concentrated in a small, well-defined spot – see Fig. 1. In surgical applications, tight laser focusing is desirable to maximize cutting efficiency and precision; yet, focusing can be hard to perform manually, as even slight variations (< 1 mm) in the focal distance can significantly affect the spot size. Motivated by these challenges, Kundrat and Schoob [3] recently introduced a technique to robotically maintain constant focal distance, thus enabling accurate, consistent cutting. In another study, Geraldes et al. [4] developed an automatic focus control system based on a miniaturized varifocal mirror, and they obtained spot sizes as small as 380 μm for a CO2 laser beam. Whereas previous work has mainly dealt with the problem of creating – and maintaining – small laser spots, in this paper we propose to study the utility of defocusing surgical lasers. In clinical practice, physicians defocus a laser beam whenever they wish to change its effect from cutting to heating – e.g., to thermally seal a blood vessel [5]. To the best of our knowledge, no previous work has studied the problem of robotically regulating the laser focus to achieve controlled tissue heating, which is precisely the contribution of the present manuscript. In the following sections, we first briefly review the dynamics of thermal laser-tissue interactions and then propose a controller capable of heating tissue according to a prescribed temperature profile. Laser-tissue interactions are generally considered hard to control due to the inherent inhomogeneity of biological tissue [6], which can create significant variability in its thermal response to laser irradiation. In this paper, we use methods from nonlinear control theory to synthesize a temperature controller capable of working on virtually any tissue type without any prior knowledge of its physical properties.

 

Motion tracking interfaces are intuitive for free-form teleoperation tasks. However, efficient manipulation control can be difficult with such interfaces because of issues like the interference of unintended motions and the limited precision of human motion control. The limitation in control efficiency reduces the operator's performance and increases their workload and frustration during robot teleoperation. To improve the efficiency, we proposed separating controlled degrees of freedom (DoFs) and adjusting the motion scaling ratio of a motion tracking interface. The motion tracking of handheld controllers from a Virtual Reality system was used for the interface. We separated the translation and rotational control into: 1) two controllers held in the dominant and non-dominant hands and 2) hand pose tracking and trackpad inputs of a controller. We scaled the control mapping ratio based on 1) the environmental constraints and 2) the teleoperator's control speed. We further conducted a user study to investigate the effectiveness of the proposed methods in increasing efficiency. Our results show that the separation of position and orientation control into two controllers and the environment-based scaling methods perform better than their alternatives. 

Combining laser technology with robotic precision and accuracy promises to introduce significant advances in minimally invasive surgical interventions. Lasers have already become a widespread tool in numerous surgical applications. They are proposed as a replacement for traditional tools (i.e., scalpels and electrocautery devices) to minimize surgical trauma, decrease healing times, and reduce the risk of postoperative complications. Compared to other energy sources, laser energy is wavelength‐dependent, allowing for preferential energy absorption in specific tissue types. This potentially leads to minimizing damage to healthy tissue and increasing surgical outcomes control and quality. Merging robotic control with laser techniques can help physicians achieve more accurate laser aiming and pave the way to automatic control of laser–tissue interactions in closed loop. Herein, a review of the state‐of‐the‐art robotic systems for laser surgery is presented. The goals of this paper are to present recent contributions in advanced intelligent systems for robot‐assisted laser surgery, provide readers with a better understanding of laser optics and the physics of laser–tissue interactions, discuss clinical applications of lasers in surgery, and provide guidance for future systems design.