Experimental Validation of Contact Dynamics for In-Hand Manipulation

This paper evaluates state-of-the-art contact models at predicting the motions and forces involved in simple in-hand robotic manipulations. In particular it focuses on three primitive actions --linear sliding, pivoting, and rolling-- that involve contacts between a gripper, a rigid object, and their environment. The evaluation is done through thousands of controlled experiments designed to capture the motion of object and gripper, and all contact forces and torques at 250Hz. We demonstrate that a contact modeling approach based on Coulomb's friction law and maximum energy principle is effective at reasoning about interaction to first order, but limited for making accurate predictions. We attribute the major limitations to 1) the non-uniqueness of force resolution inherent to grasps with multiple hard contacts of complex geometries, 2) unmodeled dynamics due to contact compliance, and 3) unmodeled geometries dueto manufacturing defects.Comment: International Symposium on Experimental Robotics, ISER 2016, Tokyo, Japa

Modelling and Controlling the Compliance of a Robotic Hand with Soft Finger-pads

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Bio-inspired friction switches: adaptive pulley systems

Frictional influences in tendon-driven robotic systems are generally unwanted, with efforts towards minimizing them where possible. In the human hand however, the tendon-pulley system is found to be frictional with a difference between high-loaded static post-eccentric and post-concentric force production of 9-12% of the total output force. This difference can be directly attributed to tendon-pulley friction. Exploiting this phenomenon for robotic and prosthetic applications we can achieve a reduction of actuator size, weight and consequently energy consumption. In this study, we present the design of a bio-inspired friction switch. The adaptive pulley is designed to minimize the influence of frictional forces under low and medium-loading conditions and maximize it under high-loading conditions. This is achieved with a dual-material system that consists of a high-friction silicone substrate and low-friction polished steel pins. The system, designed to switch its frictional properties between the low-loaded and high-loaded conditions, is described and its behavior experimentally validated with respect to the number and spacing of pins. The results validate its intended behavior, making it a viable choice for robotic tendon-driven systems.Comment: Conference. First submission, before review

3D printed flexure hinges for soft monolithic prosthetic fingers

Mechanical compliance is one of the primary properties of structures in nature playing a key role in their efficiency. This study investigates a number of commonly used flexure hinges to determine a flexure hinge morphology, which generates large displacements under a lowest possible force input. The aim of this is to design a soft and monolithic robotic finger. Fused deposition modeling, a low-cost 3D printing technique, was used to fabricate the flexure hinges and the soft monolithic robotic fingers. Experimental and finite element analyses suggest that a nonsymmetric elliptical flexure hinge is the most suitable type for use in the soft monolithic robotic finger. Having estimated the effective elastic modulus, flexion of the soft monolithic robotic fingers was simulated and this showed a good correlation with the actual experimental results. The soft monolithic robotic fingers can be employed to handle objects with unknown shapes and are also potential low-cost candidates for establishing soft and one-piece prosthetic hands with light weight. A three-finger gripper has been constructed using the identified flexure hinge to handle objects with irregular shapes such as agricultural products

A novel design process of low cost 3D printed ambidextrous finger designed for an ambidextrous robotic hand

This paper presents the novel mechanical design of an ambidextrous finger specifically designed for an ambidextrous anthropomorphic robotic hand actuated by pneumatic artificial muscles. The ambidextrous nature of design allows fingers to perform both left and right hand movements. The aim of our design is to reduce the number of actuators, increase the range of movements with best possible range ideally greater than a common human finger. Four prototypes are discussed in this paper; first prototype is focused on the choice of material and to consider the possible ways to reduce friction. Second prototype is designed to investigate the tendons routing configurations. Aim of third and fourth prototype is to improve the overall performance and to maximize the grasping force. Finally, a unified design (Final design) is presented in great detail. Comparison of all prototypes is done from different angles to evaluate the best design. The kinematic features of intermediate mode have been analysed to optimize both the flexibility and the robustness of the system, as well as to minimize the number of pneumatic muscles. The final design of an ambidextrous finger has developed, tested and 3D printed

3D printed pneumatic soft actuators and sensors: their modeling, performance quantification, control and applications in soft robotic systems

Continued technological progress in robotic systems has led to more applications where robots and humans operate in close proximity and even physical contact in some cases. Soft robots, which are primarily made of highly compliant and deformable materials, provide inherently safe features, unlike conventional robots that are made of stiff and rigid components. These robots are ideal for interacting safely with humans and operating in highly dynamic environments. Soft robotics is a rapidly developing field exploiting biomimetic design principles, novel sensor and actuation concepts, and advanced manufacturing techniques. This work presents novel soft pneumatic actuators and sensors that are directly 3D printed in one manufacturing step without requiring postprocessing and support materials using low-cost and open-source fused deposition modeling (FDM) 3D printers that employ an off-the-shelf commercially available soft thermoplastic poly(urethane) (TPU). The performance of the soft actuators and sensors developed is optimized and predicted using finite element modeling (FEM) analytical models in some cases. A hyperelastic material model is developed for the TPU based on its experimental stress-strain data for use in FEM analysis. The novel soft vacuum bending (SOVA) and linear (LSOVA) actuators reported can be used in diverse robotic applications including locomotion robots, adaptive grippers, parallel manipulators, artificial muscles, modular robots, prosthetic hands, and prosthetic fingers. Also, the novel soft pneumatic sensing chambers (SPSC) developed can be used in diverse interactive human-machine interfaces including wearable gloves for virtual reality applications and controllers for soft adaptive grippers, soft push buttons for science, technology, engineering, and mathematics (STEM) education platforms, haptic feedback devices for rehabilitation, game controllers and throttle controllers for gaming and bending sensors for soft prosthetic hands. These SPSCs are directly 3D printed and embedded in a monolithic soft robotic finger as position and touch sensors for real-time position and force control. One of the aims of soft robotics is to design and fabricate robotic systems with a monolithic topology embedded with its actuators and sensors such that they can safely interact with their immediate physical environment. The results and conclusions of this thesis have significantly contributed to the realization of this aim

Bio-inspired soft robotic systems: Exploiting environmental interactions using embodied mechanics and sensory coordination

Despite the widespread development of highly intelligent robotic systems exhibiting great precision, reliability, and dexterity, robots remain incapable of performing basic manipulation tasks that humans take for granted. Manipulation in unstructured environments continues to be acknowledged as a significant challenge. Soft robotics, the use of less rigid materials in robots, has been proposed as one means of addressing these limitations. The technique enables more compliant interactions with the environment, allowing for increasingly adaptive behaviours better suited to more human-centric applications. Embodied intelligence is a biologically inspired concept in which intelligence is a function of the entire system, not only the controller or `brain'. This thesis focuses on the use of embodied intelligence for the development of soft robots, with a particular focus on how it can aid both perception and adaptability. Two main hypotheses are raised: first, that the mechanical design and fabrication of soft-rigid hybrid robots can enable increasingly environmentally adaptive behaviours, and second, that sensing materials and morphology can provide intelligence that assists perception through embodiment. A number of approaches and frameworks for the design and development of embodied systems are presented that address these hypotheses. It is shown how embodiment in soft sensor morphology can be used to perform localised processing and thereby distribute the intelligence over the body of a system. Specifically in soft robots, sensor morphology utilises the directional deformations created by interactions with the environment to aid in perception. Building on and formalising these ideas, a number of morphology-based frameworks are proposed for detecting different stimuli. The multifaceted role of materials in soft robots is demonstrated through the development of materials capable of both sensing and changes in material property. Such materials provide additional functionality beyond their integral scaffolding and static mechanical characteristics. In particular, an integrated material has been created exhibiting both sensing capabilities and also variable stiffness and `tack’ force, thereby enabling complex single-point grasping. To maximise the intelligence that can be gained through embodiment, a design approach to soft robots, `soft-rigid hybrid' design is introduced. This approach exploits passive behaviours and body dynamics to provide environmentally adaptive behaviours and sensing. It is leveraged by multi-material 3D printing techniques and novel approaches and frameworks for designing mechanical structures. The findings in this thesis demonstrate that an embodied approach to soft robotics provides capabilities and behaviours that are not currently otherwise achievable. Utilising the concept of `embodiment' results in softer robots with an embodied intelligence that aids perception and adaptive behaviours, and has the potential to bring the physical abilities of robots one step closer to those of animals and humans.EPSR

Objekt-Manipulation und Steuerung der Greifkraft durch Verwendung von Taktilen Sensoren

This dissertation describes a new type of tactile sensor and an improved version of the dynamic tactile sensing approach that can provide a regularly updated and accurate estimate of minimum applied forces for use in the control of gripper manipulation. The pre-slip sensing algorithm is proposed and implemented into two-finger robot gripper. An algorithm that can discriminate between types of contact surface and recognize objects at the contact stage is also proposed. A technique for recognizing objects using tactile sensor arrays, and a method based on the quadric surface parameter for classifying grasped objects is described. Tactile arrays can recognize surface types on contact, making it possible for a tactile system to recognize translation, rotation, and scaling of an object independently.Diese Dissertation beschreibt eine neue Art von taktilen Sensoren und einen verbesserten Ansatz zur dynamischen Erfassung von taktilen daten, der in regelmäßigen Zeitabständen eine genaue Bewertung der minimalen Greifkraft liefert, die zur Steuerung des Greifers nötig ist. Ein Berechnungsverfahren zur Voraussage des Schlupfs, das in einen Zwei-Finger-Greifarm eines Roboters eingebaut wurde, wird vorgestellt. Auch ein Algorithmus zur Unterscheidung von verschiedenen Oberflächenarten und zur Erkennung von Objektformen bei der Berührung wird vorgestellt. Ein Verfahren zur Objekterkennung mit Hilfe einer Matrix aus taktilen Sensoren und eine Methode zur Klassifikation ergriffener Objekte, basierend auf den Daten einer rechteckigen Oberfläche, werden beschrieben. Mit Hilfe dieser Matrix können unter schiedliche Arten von Oberflächen bei Berührung erkannt werden, was es für das Tastsystem möglich macht, Verschiebung, Drehung und Größe eines Objektes unabhängig voneinander zu erkennen