Highly Manoeuvrable Eversion Robot Based on Fusion of Function with Structure

Despite their soft and compliant bodies, most of today’s soft robots have limitations when it comes to elongation or extension of their main structure. In contrast to this, a new type of soft robot called the eversion robot can grow longitudinally, exploiting the principle of eversion. Eversion robots can squeeze through narrow openings, giving the possibility to access places that are inaccessible by conventional robots. The main drawback of these types of robots is their limited bending capability due to the tendency to move along a straight line. In this paper, we propose a novel way to fuse bending actuation with the robot’s structure. We devise an eversion robot whose body forms both the central chamber that acts as the backbone as well as the actuators that cause bending and manoeuvre the manipulator. The proposed technique shows a significantly improved bending capability compared to externally attaching actuators to an eversion robot showing a 133% improvement in bending angle. Due to the increased manoeuvrability, the proposed solution is a step towards the employment of eversion robots in remote and difficult-to-access environments

Gemini Telepresence Robot System Design: A Low-Cost Solution for Manipulation and Enhanced Perception of Telepresence Robots

Current telepresence robots are costly and only allow the operator to see the environment on a 2D screen and move around on a wheelbase. Thus, these telepresence devices are severely limited because of the high barrier of entry, and the operator is unable to manipulate objects or easily perceive the world in 3D. Therefore, to address these gaps in capabilities, Gemini, an open-source telepresence humanoid robot and interface station, was designed to grant the operator the ability to manipulate objects, expand the human interface by putting the user in the 3D world with the use of a virtual reality (VR) headset, and be low-cost. The simplistic, low-cost, and intuitive controls of Gemini promote early adoption by businesses and medical personnel to grant increased telepresence needs. In addition, this platform can be utilized by robotics enthusiasts and university researchers studying humanoid robotics or human-robot interaction. This paper presents an overview of the Gemini robot’s mechanical, electrical, and programmatic systems. Upon completion of this study, it was found that Gemini was able to grant the ability to manipulate objects, increase user perception with intuitive controls, in addition to costing approximately 30% less than commercial telepresence robots. Furthermore, the paper is concluded with remarks on future iterations of the project

Electrohydrodynamic and Aerosol Jet Printing for the Copatterning of Polydimethylsiloxane and Graphene Platelet Inks

The performance of soft sensing and actuation devices is dependent on their design, the electro‐mechanical response of materials, and the ability to copattern structural and functional features. For film based soft structures, such as wearable sensors and artificial muscles, manufacturing challenges exist that prevent the translation of technology from laboratory to practical application. In this work, a hybrid manufacturing technique is presented that integrates electro‐hydrodynamic and aerosol jet deposition to print multilayer, multimaterial structures. The combined approach overcomes the respective rheological constraints of the individual processes, while presenting a pathway to higher resolution computer‐controlled patterning. Electro‐hydrodynamic deposition of a polydimethylsiloxane elastomer is demonstrated and characterized, before being combined with aerosol jet deposition of a graphene platelet ink to produce functional devices. A proof‐of‐concept, multilayer capacitive sensor is presented as a first demonstration of the manufacturing technology

How ornithopters can perch autonomously on a branch

Flapping wings are a bio-inspired method to produce lift and thrust in aerial robots, leading to quiet and efficient motion. The advantages of this technology are safety and maneuverability, and physical interaction with the environment, humans, and animals. However, to enable substantial applications, these robots must perch and land. Despite recent progress in the perching field, flapping-wing vehicles, or ornithopters, are to this day unable to stop their flight on a branch. In this paper, we present a novel method that defines a process to reliably and autonomously land an ornithopter on a branch. This method describes the joint operation of a flapping-flight controller, a close-range correction system and a passive claw appendage. Flight is handled by a triple pitch-yaw-altitude controller and integrated body electronics, permitting perching at 3 m/s. The close-range correction system, with fast optical branch sensing compensates for position misalignment when landing. This is complemented by a passive bistable claw design can lock and hold 2 Nm of torque, grasp within 25 ms and can re-open thanks to an integrated tendon actuation. The perching method is supplemented by a four-step experimental development process which optimizes for a successful design. We validate this method with a 700 g ornithopter and demonstrate the first autonomous perching flight of a flapping-wing robot on a branch, a result replicated with a second robot. This work paves the way towards the application of flapping-wing robots for long-range missions, bird observation, manipulation, and outdoor flight

Intelligent upper-limb exoskeleton using deep learning to predict human intention for sensory-feedback augmentation

The age and stroke-associated decline in musculoskeletal strength degrades the ability to perform daily human tasks using the upper extremities. Although there are a few examples of exoskeletons, they need manual operations due to the absence of sensor feedback and no intention prediction of movements. Here, we introduce an intelligent upper-limb exoskeleton system that uses cloud-based deep learning to predict human intention for strength augmentation. The embedded soft wearable sensors provide sensory feedback by collecting real-time muscle signals, which are simultaneously computed to determine the user's intended movement. The cloud-based deep-learning predicts four upper-limb joint motions with an average accuracy of 96.2% at a 200-250 millisecond response rate, suggesting that the exoskeleton operates just by human intention. In addition, an array of soft pneumatics assists the intended movements by providing 897 newton of force and 78.7 millimeter of displacement at maximum. Collectively, the intent-driven exoskeleton can augment human strength by 5.15 times on average compared to the unassisted exoskeleton. This report demonstrates an exoskeleton robot that augments the upper-limb joint movements by human intention based on a machine-learning cloud computing and sensory feedback.Comment: 15 pages, 6 figures, 1 table, Submitted for possible publicatio

Performance enhancement of the soft robotic segment for a trunk-like arm

Introduction: Trunk-like continuum robots have wide applications in manipulation and locomotion. In particular, trunk-like soft arms exhibit high dexterity and adaptability very similar to the creatures of the natural world. However, owing to the continuum and soft bodies, their performance in payload and spatial movements is limited.Methods: In this paper, we investigate the influence of key design parameters on robotic performance. It is verified that a larger workspace, lateral stiffness, payload, and bending moment could be achieved with adjustments to soft materials’ hardness, the height of module segments, and arrayed radius of actuators.Results: Especially, a 55% increase in arrayed radius would enhance the lateral stiffness by 25% and a bending moment by 55%. An 80% increase in segment height would enlarge 112% of the elongation range and 70 % of the bending range. Around 200% and 150% increments in the segment’s lateral stiffness and payload forces, respectively, could be obtained by tuning the hardness of soft materials. These relations enable the design customization of trunk-like soft arms, in which this tapering structure ensures stability via the stocky base for an impact reduction of 50% compared to that of the tip and ensures dexterity of the long tip for a relatively larger bending range of over 400% compared to that of the base.Discussion: The complete methodology of the design concept, analytical models, simulation, and experiments is developed to offer comprehensive guidelines for trunk-like soft robotic design and enable high performance in robotic manipulation

Energy shaping control of soft continuum manipulators with in-plane disturbances

Soft continuum manipulators offer levels of compliance and inherent safety that can render thema superior alternative to conventional rigid robotsfor a variety of tasks, such as medical interventions or human-robot interaction. However, the ability of soft continuum manipulators to compensate external disturbances need to be further enhanced to meet the stringent requirements of many practical applications.In this paper, we investigate the control problem forsoft continuum manipulators that consist of one inextensible segmentof constant section, which bends under the effect of the internal pressure and is subject to unknown disturbances acting in the plane of bending. A rigid-link model of the manipulatorwith a single input pressureis employed for control purposes and an energy-shaping approach isproposedto derive thecontrol law. A method for the adaptive estimation of disturbances is detailed and a disturbance compensation strategy is proposed.Finally, the effectiveness of the controlleris demonstrated with simulations and with experiments on an inextensible soft continuum manipulator that employs pneumatic actuation