Charles Baur

Robot, Asker of Questions

Collaborative control is a teleoperation system model based on human–robot dialogue. With this model, the robot asks questions to the human in order to obtain assistance with cognition and perception. This enables the human to function as a resource for the robot and help to compensate for limitations of autonomy. To understand how collaborative control influences human–robot interaction, we performed a user study based on contextual inquiry (CI). The study revealed that: (1) dialogue helps users understand problems encountered by the robot and (2) human assistance is a limited resource that must be carefully managed.

Advanced Interfaces for Vehicle Teleoperation: Collaborative Control, Sensor Fusion Displays, and Remote Driving Tools

We are working to make vehicle teleoperation accessible to all users, novices and experts alike. In our research, we are developing a new control model for teleoperation, sensor-fusion displays and a suite of remote driving tools. Our goal is to build a framework which enables humans and robots to communicate, to exchange ideas and to resolve differences. In short, to develop systems in which humans and robots work together and jointly solve problems.

Active: A Unified Platform for Building Intelligent Web Interaction Assistants

Computer systems keep growing in complexity, processing power and Web connectivity. To leverage this rich environment and to better assist users, a new type of intelligent assistant software is required. Building intelligent assistants is a difficult task that requires expertise in many AI and engineering related fields. We believe that providing a unified tool and a set of associated methodologies to create end-to-end intelligent software will bring many benefits to this area of research. Our solution, the Active framework, introduces the original concept of active ontologies to model and implement intelligent applications in a single and coherent software environment. As an example, this paper illustrates how Active has been used to create an intelligent assistant to help mobile users retrieve online information using a multimodal dialog approach

A navigation system for open liver surgery: design, workflow and first clinical applications

The surgical treatment of liver tumours relies on precise localization of the lesions and detailed knowledge of the patient‐specific vascular and biliary anatomy. Detailed three‐dimensional (3D) anatomical information facilitates complete tumour removal while preserving a sufficient amount of functional liver tissue.

Collaboration, Dialogue, Human-Robot Interaction

Teleoperation can be improved if humans and robots work as partners, exchanging information and assisting one another to achieve common goals. In this paper, we discuss the importance of collaboration and dialogue in human-robot systems. We then present collaborative control, a system model in which human and robot collaborate, and describe its use in vehicle teleoperation.

Effective vehicle teleoperation on the World Wide Web

Our goal is to make vehicle teleoperation accessible to all users. To do this, we develop easy-to-use yet capable Web tools which enable efficient, robust teleoperation in unknown and unstructured environments. Web-based teleoperation, however, raises many research issues, as well as prohibiting the use of traditional approaches. Thus, it is essential to develop new methods which minimize bandwidth usage, which provide sensor fusion displays, and which optimize human-computer interaction. We believe that existing systems do not adequately address these issues and have severely limited capability and performance as a result. In this paper we present a system design for safe and reliable Web-based vehicle teleoperation, describe an active and dynamic user interface, and explain how our approach differs from existing systems.

ROBOT AS PARTNER: VEHICLE TELEOPERATION WITH COLLABORATIVE CONTROL

We have developed a new teleoperation system model called collaborative control. With this model, the robot asks the human questions, to obtain assistance with cognition and perception during task execution. This enables the human to support the robot and to compensate for inadequacies in autonomy. In the following, we review the system models conventionally used in teleoperation, describe collaborative control, and discuss its use.

Biopsy Navigator: A Smart Haptic Interface for Interventional Radiological Gestures

Abstract The VRAI group at EPFL is conducting research in the fields of virtual reality and haptics (force-feedback) for medical applications. In particular, we have developed visualization techniques for medical images from various sources, and a high-performance haptic interface. In this paper, we present a technique that combines visualization with haptic rendering to provide real-time assistance to medical gestures. To demonstrate this technique, we have developed the BiopsyNavigator, a system that provides haptic feedback to the surgeon using patient specific data. Before the biopsy, it provides the surgeon with the ability to simulate the intervention. During the biopsy, haptic feedback is used to first help the surgeon to find the target and to define the optimal trajectory, then to physically guide the surgical gesture along the chosen path. Finally, haptic information is used to indicate that the target has been reached. Future developments will include real-time update of the patient model from various sources, including C-arm mounted CT and ultrasonic probes.

Interactive rendering of deformable objects based on a filling sphere modeling approach

Mass-spring systems have widely and effectively been used for modeling in real-time deformable objects. Easier to implement and faster than finite elements, these systems, on the other side, suffer from several drawbacks when coming to render physically believable behaviors. Neither isotropic or anisotropic materials can be controlled easily and the large number of springs and mass points composing the model makes it fastidious to define parameters to control elongation, flexion and torsion at a macroscopic level. Another weakness is that most of the materials found in nature maintain a constant or quasi-constant volume during deformations; unfortunately, mass-spring models do not have this property. In this paper, we extend the current state-of-the-art in soft tissue simulation by introducing a six-degree of freedom macroscopic elastic sphere described by mass, inertia and volumetric properties. Spheres are placed along the medial axis transform of the object whose centers are connected by a skeleton composed of a set of three-dimensional elastic links. Spheres represent internal mass, volume and control the global deformation of the object. The surface is modeled by setting point masses on the mesh nodes and damped springs on the mesh edges. These nodes are connected to the skeleton by individual elastic links, which control volume conservation and transfer forces between the surface and volumetric model. Using this framework we also present an efficient method to approximate collision detection between multiple bodies in real-time.

Markerless endoscopic registration and referencing

Accurate patient registration and referencing is a key element in navigated surgery. Unfortunately all existing methods are either invasive or very time consuming. We propose a fully non-invasive optical approach using a tracked monocular endoscope to reconstruct the surgical scene in 3D using photogrammetric methods. The 3D reconstruction can then be used for matching the pre-operative data to the intra-operative scene. In order to cope with the near real-time requirements for referencing, we use a novel, efficient 3D point management method during 3D model reconstruction. The presented prototype system provides a reconstruction accuracy of 0.1 mm and a tracking accuracy of 0.5 mm on phantom data. The ability to cope with real data is demonstrated by cadaver experiments.