A haptic platform to enable fingertip grasping and manipulation

Haptic technologies allow human users to haptically interact with virtual environments. Haptics has been employed in many application domains including operator training, virtual exploration and teleoperation. Currently, most commercially available haptic devices focus on a single point of haptic interaction. While single-point haptics have been successfully employed in many applications, they remain limited to particular types of haptic interaction. Multi-point haptic devices are a logical progression and facilitate a far wider range of interactions including object grasping, multi-finger object manipulation and size discrimination. The ability to effectively achieve such interactions offers significant benefits for many applications including virtual training, telesurgery and telemanipulation. In such applications, the ability to use multi-point haptic interactions can provide far more effective user interaction as well improved perception of the virtual environment.

A multi-point haptic platform for grasping and manipulating virtual objects

This work presents a multi-point haptic platform that employs two Phantom Omni haptic devices. A gripper attachment connects to both devices and enables multi-point haptic grasping in virtual environments. In contrast to more complex approaches, this setup benefits from low-cost, reliability, and ease of programming while being capable of independently rendering forces to each of the user’s fingertips. The ability to grasp with multiple points potentially lends itself to applications such as virtual training, telesurgery and telemanipulation.

Dynamic privacy assessment in a smart house environment using multimodal sensing

Surveillance applications in private environments such as smart houses require a privacy management policy if such systems are to be accepted by the occupants of the environment. This is due to the invasive nature of surveillance, and the private nature of the home. In this article, we propose a framework for dynamically altering the privacy policy applied to the monitoring of a smart house based on the situation within the environment. Initially the situation, or context, within the environment is determined; we identify several factors for determining environmental context, and propose methods to quantify the context using audio and binary sensor data. The context is then mapped to an appropriate privacy policy, which is implemented by applying data hiding techniques to control access to data gathered from various information sources. The significance of this work lies in the examination of privacy issues related to assisted-living smart house environments. A single privacy policy in such applications would be either too restrictive for an observer, for example, a carer, or too invasive for the occupants. We address this by proposing a dynamic method, with the aim of decreasing the invasiveness of the technology, while retaining the purpose of the system.

Sensing and using social context

We present online algorithms to extract social context: Social spheres are labeled locations of significance, represented as convex hulls extracted from GPS traces. Colocation is determined from Bluetooth and GPS to extract social rhythms, patterns in time, duration, place, and people corresponding to real-world activities. Social ties are formulated from proximity and shared spheres and rhythms. Quantitative evaluation is performed for 10+ million samples over 45 man-months. Applications are presented with assessment of perceived utility: Socio-Graph, a video and photo browser with filters for social metadata, and Jive, a blog browser that uses rhythms to discover similarity between entries automatically.

A novel sensing technique for monitoring pitting corrosion of stainless steel type 316L

A novel electrochemically integrated multi-electrode array namely the wire beam electrode(WBE) in combination with noise signatures analysis has been designed to monitor pittingcorrosion of one of the best corrosion resistance ferrous alloys, stainless steel type 316L.From the direct correlation of electrochemical potential noise signatures and galvanic currentdistribution maps during pitting corrosion processes, two characteristic noise patterns wereobserved prior to stable pit formation: (i) the characteristic ‘peak’ of rapid potential transient,towards less negative direction, followed by recovery (termed noise signature I) was found tocorrelate with the disappearance of unstable anode; (ii) the characteristic noise pattern ofquick potential changes towards less negative direction followed by no recovery (termed noisesignature II) was found to correspond with the massive disappearance of minor anodes leadingto formation of highly localized major anodes in the galvanic current distribution maps.

Function-based approach to mixed haptic effects rendering

Commonly, surface and solid haptic effects are defined in such a way that they hardly can be rendered together. We propose a method for defining mixed haptic effects including surface, solid, and force fields. These haptic effects can be applied to virtual scenes containing various objects, including polygon meshes, point clouds, impostors, and layered textures, voxel models as well as function-based shapes. Accordingly, we propose a way how to identify location of the haptic tool in such virtual scenes as well as consistently and seamlessly determine haptic effects when the haptic tool moves in the scenes with objects having different sizes, locations, and mutual penetrations. To provide for an efficient and flexible rendering of haptic effects, we propose to concurrently use explicit, implicit and parametric functions, and algorithmic procedures.

3D locomotion biomimetic robot fish with haptic feedback

This thesis developed a biomimetic robot fish and built a novel haptic robot fish system based on the kinematic modelling and three-dimentional computational fluid dynamic (CFD) hydrodynamic analysis. The most important contribution is the successful CFD simulation of the robot fish, supporting users in understanding the hydrodynamic properties around it.

Haptic microrobotic cell injection system

Microrobotic cell injection is the subject of increasing research interest. At present, an operator relies completely on visual information and can be subject to low success rates, poor repeatability, and extended training times. This paper focuses on increasing operator performance during cell injection in two ways. First, our completed haptic cell injection system aims to increase the operator's performance during real-time cell injection. Haptic bilateralism is investigated and a mapping framework provides an intuitive method for manoeuvring the micropipette in a manner similar to handheld needle insertion. Volumetric virtual fixtures are then introduced to haptically assist the operator to penetrate the cell at the desired location. The performance of the volumetric virtual fixtures is also discussed. Second, the haptically enabled cell injection system is replicated as a virtual environment facilitating virtual offline operator training. Virtual operator training utilizes the same mapping framework and haptic virtual fixtures as the physical system allowing the operator to train offline and then directly transfer their skills to real-time cell injection.