COMPARATIVE STUDY OF HAPTIC AND VISUAL FEEDBACK FOR KINESTHETIC TRAINING TASKS

Haptics is the sense of simulating and applying the sense of human touch. Application of touch sensations is done with haptic interface devices. The past few years has seen the development of several haptic interface devices with a wide variety of technologies used in their design. This thesis introduces haptic technologies and includes a survey of haptic interface devices and technologies. An improvement in simulating and applying touch sensation when using the Quanser Haptic Wand with proSense is suggested in this work using a novel five degree-of-freedom algorithm. This approach uses two additional torques to enhance the three degree-of-freedom of force feedback currently available with these products. Modern surgical trainers for performing laparoscopic surgery are incorporating haptic feedback in addition to visual feedback for training. This work presents a quantitative comparison of haptic versus visual training. One of the key results of the study is that haptic feedback is better than visual feedback for kinesthetic navigation tasks

Steering control for haptic feedback and active safety functions

Steering feedback is an important element that defines driver–vehicle interaction. It strongly affects driving performance and is primarily dependent on the steering actuator\u27s control strategy. Typically, the control method is open loop, that is without any reference tracking; and its drawbacks are hardware dependent steering feedback response and attenuated driver–environment transparency. This thesis investigates a closed-loop control method for electric power assisted steering and steer-by-wire systems. The advantages of this method, compared to open loop, are better hardware impedance compensation, system independent response, explicit transparency control and direct interface to active safety functions.The closed-loop architecture, outlined in this thesis, includes a reference model, a feedback controller and a disturbance observer. The feedback controller forms the inner loop and it ensures: reference tracking, hardware impedance compensation and robustness against the coupling uncertainties. Two different causalities are studied: torque and position control. The two are objectively compared from the perspective of (uncoupled and coupled) stability, tracking performance, robustness, and transparency.The reference model forms the outer loop and defines a torque or position reference variable, depending on the causality. Different haptic feedback functions are implemented to control the following parameters: inertia, damping, Coulomb friction and transparency. Transparency control in this application is particularly novel, which is sequentially achieved. For non-transparent steering feedback, an environment model is developed such that the reference variable is a function of virtual dynamics. Consequently, the driver–steering interaction is independent from the actual environment. Whereas, for the driver–environment transparency, the environment interaction is estimated using an observer; and then the estimated signal is fed back to the reference model. Furthermore, an optimization-based transparency algorithm is proposed. This renders the closed-loop system transparent in case of environmental uncertainty, even if the initial condition is non-transparent.The steering related active safety functions can be directly realized using the closed-loop steering feedback controller. This implies, but is not limited to, an angle overlay from the vehicle motion control functions and a torque overlay from the haptic support functions.Throughout the thesis, both experimental and the theoretical findings are corroborated. This includes a real-time implementation of the torque and position control strategies. In general, it can be concluded that position control lacks performance and robustness due to high and/or varying system inertia. Though the problem is somewhat mitigated by a robust H-infinity controller, the high frequency haptic performance remains compromised. Whereas, the required objectives are simultaneously achieved using a torque controller

Haptic Interaction with 3D oriented point clouds on the GPU

Real-time point-based rendering and interaction with virtual objects is gaining popularity and importance as di�erent haptic devices and technologies increasingly provide the basis for realistic interaction. Haptic Interaction is being used for a wide range of applications such as medical training, remote robot operators, tactile displays and video games. Virtual object visualization and interaction using haptic devices is the main focus; this process involves several steps such as: Data Acquisition, Graphic Rendering, Haptic Interaction and Data Modi�cation. This work presents a framework for Haptic Interaction using the GPU as a hardware accelerator, and includes an approach for enabling the modi�cation of data during interaction. The results demonstrate the limits and capabilities of these techniques in the context of volume rendering for haptic applications. Also, the use of dynamic parallelism as a technique to scale the number of threads needed from the accelerator according to the interaction requirements is studied allowing the editing of data sets of up to one million points at interactive haptic frame rates

Haptic rendering of continuous parametric models

Haptic rendering is the process of computing restoring forces that are required to generate a perception of touch between a user and a virtual environment. The realism of haptic rendering depends mainly on haptic rendering algorithms and the modeling of virtual objects in a virtual environment. Friction and texture rendering also play an important role in increasing the realism of the experience between a user and a virtual environment. The state of the art haptic and friction rendering algorithms in the literature are developed for polygonal models. These approaches can not benefit from the advantages of continuous parametric surfaces such as compact representation, higher order continuity and exact computation of surface normals. In this thesis, a feedback-stabilized closest point tracking based haptic rendering algorithm is extended by introducing a direct friction rendering method for continuous parametric surfaces. Unlike the existing approaches, the proposed friction rendering method is direct and does not rely on the algorithms introduced for polyhedral surfaces. This algorithm implements the stiction model of friction for haptic rendering of parametric surfaces. It can directly operate on parametric models and can handle surfaces with high curvature. Furthermore, the algorithm allows transitions from sticking to sliding and sliding to sticking, as well as surface to surface transitions, without introducing discontinuous force artifacts. The algorithm also allows for tuning of the friction coefficient during the mode transitions to enable rendering of the Stribeck effect. Thanks to its feedback-stabilized core, it is robust against drift and numerical noise. The algorithm is computationally efficient (with respect to time and space); its applicability and effectiveness to simulate friction are verified through simulations and real-time implementations. In particular, the friction rendering algorithm is tested using pre-determined trajectories that demonstrate successful rendering of static friction at a corner, the mode changes from static-to-dynamic and dynamic-to-static friction

Nonlinear position and stiffness Backstepping controller for a two Degrees of Freedom pneumatic robot

This paper presents an architecture of a 2 Degrees of Freedom pneumatic robot which can be used as a haptic interface. To improve the haptic rendering of this device, a nonlinear position and stiffness controller without force measurement based on a Backstepping synthesis is presented. Thus, the robot can follow a targeted trajectory in Cartesian position with a variable compliant behavior when disturbance forces are applied. An appropriate tuning methodology of the closed-loop stiffness and closed-loop damping of the robot is given to obtain a desired disturbance response. The models, the synthesis and the stability analysis of this controller are described in this paper. Two models are presented in this paper, the first one is an accurate simulation model which describes the mechanical behavior of the robot, the thermodynamics phenomena in the pneumatic actuators, and the servovalves characteristics. The second model is the model used to synthesize the controller. This control model is obtained by simplifying the simulation model to obtain a MIMO strict feedback form. Finally, some simulation and experimental results are given and the controller performances are discussed and compared with a classical linear impedance controller

6D Frictional Contact for Rigid Bodies

International audienceWe present a new approach to modeling contact between rigid objects that augments an individual Coulomb friction point-contact model with rolling and spinning friction constraints. Starting from the intersection volume, we compute a contact normal from the volume gradient. We compute a contact position from the first moment of the intersection volume, and approximate the extent of the contact patch from the second moment of the intersection volume. By incorporating knowledge of the contact patch into a point contact Coulomb friction formulation, we produce a 6D constraint that provides appropriate limits on torques to accommodate displacement of the center of pressure within the contact patch, while also providing a rotational torque due to dry friction to resist spinning. A collection of examples demonstrate the power and benefits of this simple formulation

Robotic manipulators for single access surgery

This thesis explores the development of cooperative robotic manipulators for enhancing surgical precision and patient outcomes in single-access surgery and, specifically, Transanal Endoscopic Microsurgery (TEM). During these procedures, surgeons manipulate a heavy set of instruments via a mechanical clamp inserted in the patient’s body through a surgical port, resulting in imprecise movements, increased patient risks, and increased operating time. Therefore, an articulated robotic manipulator with passive joints is initially introduced, featuring built-in position and force sensors in each joint and electronic joint brakes for instant lock/release capability. The articulated manipulator concept is further improved with motorised joints, evolving into an active tool holder. The joints allow the incorporation of advanced robotic capabilities such as ultra-lightweight gravity compensation and hands-on kinematic reconfiguration, which can optimise the placement of the tool holder in the operating theatre. Due to the enhanced sensing capabilities, the application of the active robotic manipulator was further explored in conjunction with advanced image guidance approaches such as endomicroscopy. Recent advances in probe-based optical imaging such as confocal endomicroscopy is making inroads in clinical uses. However, the challenging manipulation of imaging probes hinders their practical adoption. Therefore, a combination of the fully cooperative robotic manipulator with a high-speed scanning endomicroscopy instrument is presented, simplifying the incorporation of optical biopsy techniques in routine surgical workflows. Finally, another embodiment of a cooperative robotic manipulator is presented as an input interface to control a highly-articulated robotic instrument for TEM. This master-slave interface alleviates the drawbacks of traditional master-slave devices, e.g., using clutching mechanics to compensate for the mismatch between slave and master workspaces, and the lack of intuitive manipulation feedback, e.g. joint limits, to the user. To address those drawbacks a joint-space robotic manipulator is proposed emulating the kinematic structure of the flexible robotic instrument under control.Open Acces

ADD: Analytically Differentiable Dynamics for Multi-Body Systems with Frictional Contact

We present a differentiable dynamics solver that is able to handle frictional contact for rigid and deformable objects within a unified framework. Through a principled mollification of normal and tangential contact forces, our method circumvents the main difficulties inherent to the non-smooth nature of frictional contact. We combine this new contact model with fully-implicit time integration to obtain a robust and efficient dynamics solver that is analytically differentiable. In conjunction with adjoint sensitivity analysis, our formulation enables gradient-based optimization with adaptive trade-offs between simulation accuracy and smoothness of objective function landscapes. We thoroughly analyse our approach on a set of simulation examples involving rigid bodies, visco-elastic materials, and coupled multi-body systems. We furthermore showcase applications of our differentiable simulator to parameter estimation for deformable objects, motion planning for robotic manipulation, trajectory optimization for compliant walking robots, as well as efficient self-supervised learning of control policies.Comment: Moritz Geilinger and David Hahn contributed equally to this wor