TacFR-Gripper: A Reconfigurable Fin Ray-Based Compliant Robotic Gripper with Tactile Skin for In-Hand Manipulation

This paper introduces the TacFR-Gripper, a reconfigurable Fin Ray-based soft and compliant robotic gripper equipped with tactile skin, which can be used for dexterous in-hand manipulation tasks. This gripper can adaptively grasp objects of diverse shapes and stiffness levels. An array of Force Sensitive Resistor (FSR) sensors is embedded within the robotic finger to serve as the tactile skin, enabling the robot to perceive contact information during manipulation. We provide theoretical analysis for gripper design, including kinematic analysis, workspace analysis, and finite element analysis to identify the relationship between the gripper's load and its deformation. Moreover, we implemented a Graph Neural Network (GNN)-based tactile perception approach to enable reliable grasping without accidental slip or excessive force. Three physical experiments were conducted to quantify the performance of the TacFR-Gripper. These experiments aimed to i) assess the grasp success rate across various everyday objects through different configurations, ii) verify the effectiveness of tactile skin with the GNN algorithm in grasping, iii) evaluate the gripper's in-hand manipulation capabilities for object pose control. The experimental results indicate that the TacFR-Gripper can grasp a wide range of complex-shaped objects with a high success rate and deliver dexterous in-hand manipulation. Additionally, the integration of tactile skin with the GNN algorithm enhances grasp stability by incorporating tactile feedback during manipulations. For more details of this project, please view our website: https://sites.google.com/view/tacfr-gripper/homepage

Digital Fabrication Approaches for the Design and Development of Shape-Changing Displays

Interactive shape-changing displays enable dynamic representations of data and information through physically reconfigurable geometry. The actuated physical deformations of these displays can be utilised in a wide range of new application areas, such as dynamic landscape and topographical modelling, architectural design, physical telepresence and object manipulation. Traditionally, shape-changing displays have a high development cost in mechanical complexity, technical skills and time/finances required for fabrication. There is still a limited number of robust shape-changing displays that go beyond one-off prototypes. Specifically, there is limited focus on low-cost/accessible design and development approaches involving digital fabrication (e.g. 3D printing). To address this challenge, this thesis presents accessible digital fabrication approaches that support the development of shape-changing displays with a range of application examples – such as physical terrain modelling and interior design artefacts. Both laser cutting and 3D printing methods have been explored to ensure generalisability and accessibility for a range of potential users. The first design-led content generation explorations show that novice users, from the general public, can successfully design and present their own application ideas using the physical animation features of the display. By engaging with domain experts in designing shape-changing content to represent data specific to their work domains the thesis was able to demonstrate the utility of shape-changing displays beyond novel systems and describe practical use-case scenarios and applications through rapid prototyping methods. This thesis then demonstrates new ways of designing and building shape-changing displays that goes beyond current implementation examples available (e.g. pin arrays and continuous surface shape-changing displays). To achieve this, the thesis demonstrates how laser cutting and 3D printing can be utilised to rapidly fabricate deformable surfaces for shape-changing displays with embedded electronics. This thesis is concluded with a discussion of research implications and future direction for this work

Towards Declarative Safety Rules for Perception Specification Architectures

Agriculture has a high number of fatalities compared to other blue collar fields, additionally population decreasing in rural areas is resulting in decreased work force. These issues have resulted in increased focus on improving efficiency of and introducing autonomy in agriculture. Field robots are an increasingly promising branch of robotics targeted at full automation in agriculture. The safety aspect however is rely addressed in connection with safety standards, which limits the real-world applicability. In this paper we present an analysis of a vision pipeline in connection with functional-safety standards, in order to propose solutions for how to ascertain that the system operates as required. Based on the analysis we demonstrate a simple mechanism for verifying that a vision pipeline is functioning correctly, thus improving the safety in the overall system.Comment: Presented at DSLRob 2015 (arXiv:1601.00877

Digital implementation of the cellular sensor-computers

Two different kinds of cellular sensor-processor architectures are used nowadays in various applications. The first is the traditional sensor-processor architecture, where the sensor and the processor arrays are mapped into each other. The second is the foveal architecture, in which a small active fovea is navigating in a large sensor array. This second architecture is introduced and compared here. Both of these architectures can be implemented with analog and digital processor arrays. The efficiency of the different implementation types, depending on the used CMOS technology, is analyzed. It turned out, that the finer the technology is, the better to use digital implementation rather than analog

Scalable underwater assembly with reconfigurable visual fiducials

We present a scalable combined localization infrastructure deployment and task planning algorithm for underwater assembly. Infrastructure is autonomously modified to suit the needs of manipulation tasks based on an uncertainty model on the infrastructure's positional accuracy. Our uncertainty model can be combined with the noise characteristics from multiple devices. For the task planning problem, we propose a layer-based clustering approach that completes the manipulation tasks one cluster at a time. We employ movable visual fiducial markers as infrastructure and an autonomous underwater vehicle (AUV) for manipulation tasks. The proposed task planning algorithm is computationally simple, and we implement it on AUV without any offline computation requirements. Combined hardware experiments and simulations over large datasets show that the proposed technique is scalable to large areas.Comment: Submitted to ICRA 202

Homogeneous Spiking Neuromorphic System for Real-World Pattern Recognition

A neuromorphic chip that combines CMOS analog spiking neurons and memristive synapses offers a promising solution to brain-inspired computing, as it can provide massive neural network parallelism and density. Previous hybrid analog CMOS-memristor approaches required extensive CMOS circuitry for training, and thus eliminated most of the density advantages gained by the adoption of memristor synapses. Further, they used different waveforms for pre and post-synaptic spikes that added undesirable circuit overhead. Here we describe a hardware architecture that can feature a large number of memristor synapses to learn real-world patterns. We present a versatile CMOS neuron that combines integrate-and-fire behavior, drives passive memristors and implements competitive learning in a compact circuit module, and enables in-situ plasticity in the memristor synapses. We demonstrate handwritten-digits recognition using the proposed architecture using transistor-level circuit simulations. As the described neuromorphic architecture is homogeneous, it realizes a fundamental building block for large-scale energy-efficient brain-inspired silicon chips that could lead to next-generation cognitive computing.Comment: This is a preprint of an article accepted for publication in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol 5, no. 2, June 201