1,685 research outputs found

    Study and development of sensorimotor interfaces for robotic human augmentation

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    This thesis presents my research contribution to robotics and haptics in the context of human augmentation. In particular, in this document, we are interested in bodily or sensorimotor augmentation, thus the augmentation of humans by supernumerary robotic limbs (SRL). The field of sensorimotor augmentation is new in robotics and thanks to the combination with neuroscience, great leaps forward have already been made in the past 10 years. All of the research work I produced during my Ph.D. focused on the development and study of fundamental technology for human augmentation by robotics: the sensorimotor interface. This new concept is born to indicate a wearable device which has two main purposes, the first is to extract the input generated by the movement of the user's body, and the second to provide the somatosensory system of the user with an haptic feedback. This thesis starts with an exploratory study of integration between robotic and haptic devices, intending to combine state-of-the-art devices. This allowed us to realize that we still need to understand how to improve the interface that will allow us to feel the agency when using an augmentative robot. At this point, the path of this thesis forks into two alternative ways that have been adopted to improve the interaction between the human and the robot. In this regard, the first path we presented tackles two aspects conerning the haptic feedback of sensorimotor interfaces, which are the choice of the positioning and the effectiveness of the discrete haptic feedback. In the second way we attempted to lighten a supernumerary finger, focusing on the agility of use and the lightness of the device. One of the main findings of this thesis is that haptic feedback is considered to be helpful by stroke patients, but this does not mitigate the fact that the cumbersomeness of the devices is a deterrent to their use. Preliminary results here presented show that both the path we chose to improve sensorimotor augmentation worked: the presence of the haptic feedback improves the performance of sensorimotor interfaces, the co-positioning of haptic feedback and the input taken from the human body can improve the effectiveness of these interfaces, and creating a lightweight version of a SRL is a viable solution for recovering the grasping function

    Intuitive Hand Teleoperation by Novice Operators Using a Continuous Teleoperation Subspace

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    Human-in-the-loop manipulation is useful in when autonomous grasping is not able to deal sufficiently well with corner cases or cannot operate fast enough. Using the teleoperator's hand as an input device can provide an intuitive control method but requires mapping between pose spaces which may not be similar. We propose a low-dimensional and continuous teleoperation subspace which can be used as an intermediary for mapping between different hand pose spaces. We present an algorithm to project between pose space and teleoperation subspace. We use a non-anthropomorphic robot to experimentally prove that it is possible for teleoperation subspaces to effectively and intuitively enable teleoperation. In experiments, novice users completed pick and place tasks significantly faster using teleoperation subspace mapping than they did using state of the art teleoperation methods.Comment: ICRA 2018, 7 pages, 7 figures, 2 table

    Autonomy Infused Teleoperation with Application to BCI Manipulation

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    Robot teleoperation systems face a common set of challenges including latency, low-dimensional user commands, and asymmetric control inputs. User control with Brain-Computer Interfaces (BCIs) exacerbates these problems through especially noisy and erratic low-dimensional motion commands due to the difficulty in decoding neural activity. We introduce a general framework to address these challenges through a combination of computer vision, user intent inference, and arbitration between the human input and autonomous control schemes. Adjustable levels of assistance allow the system to balance the operator's capabilities and feelings of comfort and control while compensating for a task's difficulty. We present experimental results demonstrating significant performance improvement using the shared-control assistance framework on adapted rehabilitation benchmarks with two subjects implanted with intracortical brain-computer interfaces controlling a seven degree-of-freedom robotic manipulator as a prosthetic. Our results further indicate that shared assistance mitigates perceived user difficulty and even enables successful performance on previously infeasible tasks. We showcase the extensibility of our architecture with applications to quality-of-life tasks such as opening a door, pouring liquids from containers, and manipulation with novel objects in densely cluttered environments

    A Cost-Effective Haptic Device for Assistive and Rehabilitation Purposes

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    With the growing population of elderly, the need for assistance has also increased considerably especially for the tasks such as cleaning, reaching and grasping objects among others. There are numerous assistive devices in the market for this group of people. However, they are either too expensive or require overwhelming user effort for manipulation. Therefore, the presented research is primarily concerned with developing a low-cost, easy to use assistive device for elderly to reach and grasp objects through intuitive interface for the control of a slave anthropomorphic robotic arm (tele operator). The system also implements haptic feedback technology that enables the user to maneuver the grasping task in a realistic manner. A bilateral master-slave robotic system combined with the haptic feedback technology has been designed, built and tested to determine the suitability of this device for the chosen application. The final prototype consists of primarily off the shelf components programmed in such a way as to provide accurate teleoperation and haptic feedback to the user. While the nature of the project as a prototype precluded any patient trials, testing of the final system has shown that a fairly low cost device can be capable of providing the user an ability to remotely control a robotic arm for reaching and grasping objects with accurate force feedback

    Towards Reuse and Recycling of Lithium-ion Batteries: Tele-robotics for Disassembly of Electric Vehicle Batteries

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    Disassembly of electric vehicle batteries is a critical stage in recovery, recycling and re-use of high-value battery materials, but is complicated by limited standardisation, design complexity, compounded by uncertainty and safety issues from varying end-of-life condition. Telerobotics presents an avenue for semi-autonomous robotic disassembly that addresses these challenges. However, it is suggested that quality and realism of the user's haptic interactions with the environment is important for precise, contact-rich and safety-critical tasks. To investigate this proposition, we demonstrate the disassembly of a Nissan Leaf 2011 module stack as a basis for a comparative study between a traditional asymmetric haptic-'cobot' master-slave framework and identical master and slave cobots based on task completion time and success rate metrics. We demonstrate across a range of disassembly tasks a time reduction of 22%-57% is achieved using identical cobots, yet this improvement arises chiefly from an expanded workspace and 1:1 positional mapping, and suffers a 10-30% reduction in first attempt success rate. For unbolting and grasping, the realism of force feedback was comparatively less important than directional information encoded in the interaction, however, 1:1 force mapping strengthened environmental tactile cues for vacuum pick-and-place and contact cutting tasks.Comment: 21 pages, 12 figures, Submitted to Frontiers in Robotics and AI; Human-Robot Interactio

    Increasing Transparency and Presence of Teleoperation Systems Through Human-Centered Design

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    Teleoperation allows a human to control a robot to perform dexterous tasks in remote, dangerous, or unreachable environments. A perfect teleoperation system would enable the operator to complete such tasks at least as easily as if he or she was to complete them by hand. This ideal teleoperator must be perceptually transparent, meaning that the interface appears to be nearly nonexistent to the operator, allowing him or her to focus solely on the task environment, rather than on the teleoperation system itself. Furthermore, the ideal teleoperation system must give the operator a high sense of presence, meaning that the operator feels as though he or she is physically immersed in the remote task environment. This dissertation seeks to improve the transparency and presence of robot-arm-based teleoperation systems through a human-centered design approach, specifically by leveraging scientific knowledge about the human motor and sensory systems. First, this dissertation aims to improve the forward (efferent) teleoperation control channel, which carries information from the human operator to the robot. The traditional method of calculating the desired position of the robot\u27s hand simply scales the measured position of the human\u27s hand. This commonly used motion mapping erroneously assumes that the human\u27s produced motion identically matches his or her intended movement. Given that humans make systematic directional errors when moving the hand under conditions similar to those imposed by teleoperation, I propose a new paradigm of data-driven human-robot motion mappings for teleoperation. The mappings are determined by having the human operator mimic the target robot as it autonomously moves its arm through a variety of trajectories in the horizontal plane. Three data-driven motion mapping models are described and evaluated for their ability to correct for the systematic motion errors made in the mimicking task. Individually-fit and population-fit versions of the most promising motion mapping model are then tested in a teleoperation system that allows the operator to control a virtual robot. Results of a user study involving nine subjects indicate that the newly developed motion mapping model significantly increases the transparency of the teleoperation system. Second, this dissertation seeks to improve the feedback (afferent) teleoperation control channel, which carries information from the robot to the human operator. We aim to improve a teleoperation system a teleoperation system by providing the operator with multiple novel modalities of haptic (touch-based) feedback. We describe the design and control of a wearable haptic device that provides kinesthetic grip-force feedback through a geared DC motor and tactile fingertip-contact-and-pressure and high-frequency acceleration feedback through a pair of voice-coil actuators mounted at the tips of the thumb and index finger. Each included haptic feedback modality is known to be fundamental to direct task completion and can be implemented without great cost or complexity. A user study involving thirty subjects investigated how these three modalities of haptic feedback affect an operator\u27s ability to control a real remote robot in a teleoperated pick-and-place task. This study\u27s results strongly support the utility of grip-force and high-frequency acceleration feedback in teleoperation systems and show more mixed effects of fingertip-contact-and-pressure feedback

    A Human Gesture Mapping Method to Control a Multi‐Functional Hand for Robot‐Assisted Laparoscopic Surgery: The MUSHA Case

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    This work presents a novel technique to control multi-functional hand for robot-assisted laparoscopic surgery. We tested the technique using the MUSHA multi-functional hand, a robot-aided minimally invasive surgery tool with more degrees of freedom than the standard commercial end-effector of the da Vinci robot. Extra degrees of freedom require the development of a proper control strategy to guarantee high performance and avoid an increasing complexity of control consoles. However, developing reliable control algorithms while reducing the control side's mechanical complexity is still an open challenge. In the proposed solution, we present a control strategy that projects the human hand motions into the robot actuation space. The human hand motions are tracked by a LeapMotion camera and mapped into the actuation space of the virtualized end-effector. The effectiveness of the proposed method was evaluated in a twofold manner. Firstly, we verified the Lyapunov stability of the algorithm, then an user study with 10 subjects assessed the intuitiveness and usability of the system

    Command Acknowledge through Tactile Feedback Improves the Usability of an EMG-based Interface for the Frontalis Muscle

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    This work presents a study on the effectiveness of tactile feedback for the acknowledgement of a correct command detection in an EMG-based interface for the frontalis muscle. EMG interfaces are increasingly used in assistive robotics to control robots exploiting the repeatability and robustness of the electromyographic signal. However, in many application a feedback about the correct detection of an input is often missed and the user has to wait for the device motion in order to understand if his/her will has been correctly detected by the system. We demonstrate with a user study involving fifteen subjects, that a simple vibrotactile feedback can reduce the muscular effort and the time needed to execute a sequence of action commanded by an EMG device. As a case study, an EMG interface for the frontalis muscle has been used, however proposed results could be extended to EMG interfaces designed for other muscles, e.g., for prosthesis or exoskeleton control

    Q&A: Robotics as a tool to understand the brain.

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