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.

Towards an efficient haptic rendering using data-driven modeling

This thesis focuses on the optimisation of haptic rendering of interactions with deformable models. The research demonstrated that data-driven techniques can produce a real-time, accurate and complex simulation experience. Applications include, but not limited to, virtual training, rapid prototyping, virtual presence, and entertainment.

Enhancing audio-haptic enabled novel dental training platform performance

Existing haptic and non-haptic dental simulators do not eliminate the problem of hand instability while using the haptic devices for training purpose. This paper reports an audio-haptic dental training platform, which uses a Hand Stability System to reduce the effect of nervousness and hand instability for trainee dental students. Maintaining the ease of implementation, application customizability and the cost factor, the proposed platform increases the training efficiency by enhancing the immersive haptic experience with hand stability. This haptic platform includes multiple angle viewing techniques, audio feedback and session recording for after action review. Trials using this preliminary platform reduced the effect of human nervousness and hand instability due to the customized design.

Wireless haptic rendering for mobile platforms

Computer haptics has so far been performed on a personal computer (PC). Off the shelf haptic devices provide only PC interfaces and software drivers for control and communication. The new wave of high capable tablet PCs and high end smart phones introduced new platforms for haptic applications. The major problem was to communicate wirelessly to provide user convenience and support mobility which is an essential feature for these platforms. In this paper we provide a wireless layered communication protocol and a hardware setup that enables off the shelf haptic devices to communicate wirelessly with a mobile device. The layers in the protocol enable the change of any hardware components without affecting the data flow. However, the adoption of the wireless interface instead of the wired one comes with the price of speed. Haptic refresh loops require a relatively high refresh rate of 1000 Hz compared to graphics loop which require between 30 and 60 only. An interpolation algorithm was demonstrated to compensate the latency and secure a stable user experience. The introduced setup was tested against portable environments and the users could perform similar functionalities to what are available on a wired setup to a PC.

Human performance measures for interactive haptic-audio-visual interfaces

Virtual reality and simulation are becoming increasingly important in modern society and it is essential to improve our understanding of system usability and efficacy from the users’ perspective. This paper introduces a novel evaluation method designed to assess human user capability when undertaking technical and procedural training using virtual training systems. The evaluation method falls under the user-centred design and evaluation paradigm and draws on theories of cognitive, skillbased and affective learning outcomes. The method focuses on user interaction with haptic-audio-visual interfaces and the complexities related to variability in users’ performance, and the adoption and acceptance of the technologies. A large scale user study focusing on object assembly training tasks involving selecting, rotating, releasing, inserting and manipulating 3D objects was performed. The study demonstrated the advantages of the method in obtaining valuable multimodal information for accurate and comprehensive evaluation of virtual training system efficacy. The study investigated how well users learn, perform, adapt to and perceive the virtual training. The results of the study revealed valuable aspects of the design and evaluation of virtual training systems contributing to an improved understanding of more usable virtual training systems.

A framework for visual and haptic collaboration in shared virtual spaces

We propose a framework for visual and haptic collaboration in X3D/VRML shared virtual spaces. In this collaborative framework, two pipelines— visual and haptic—complement each other to provide a simple and efficient solution to problem requiring collaboration in shared virtual spaces on the web. We consider shared objects defined as virtual object with their visual and physical properties rendered synchronously on each client computer. We introduce virtual tools which are shared objects associated with interactive and haptic devices. We implemented the proposed ideas as a server-client framework with a dedicated viewer. We discuss two implementation frameworks based on the strong and thin server concepts.

Automatic deformation transfer for data-driven haptic rendering

This paper addresses a major challenge in datadriven haptic modeling of deformable objects. Data-driven modelling is done for specific objects and is difficult to generalize for nearly isometric objects that have similarities in semantics or topology. This limitation prevents the wide use of the data-driven modeling techniques when compared with parametric methods such as finite element methods. The proposed solution is to incorporate deformation transfer methods when processing similar instances. The contributions of this work are focused on the novel automatic shape correspondence method that overcomes the problems of symmetry and semantics presence requirement. The results shows that the proposed algorithm can efficiently calculate the correspondence and transfer deformations for a range of similar 3D objects.

Robotic object grasping in context of human grasping and manipulation

This paper presents experimental and deductive findings that shed new light on grasp force estimation, which improves robot’s chances to grasp and manipulate the object close to optimum conditions on the first attempt, which in turn improves robot’s object manipulation dexterity.
This paper proposes that object slippage detection in the human hand is not detected based purely on microvibrations sensed by the human skin during incipient slippage but also on load sensing at each finger and movement of fingers relative to each other while holding an object.