This paper proposes a strategy for grasp and manipulation of unknown objects. In order to derive force relations of fingers, the groped shape of soft fingers is introduced. The groped shape is not equal to the real object shape, but is tightly related to the force equilibrium of fingers. By considering contact forces of the groped shape, a simple control parameters can be derived. The manipulation of an object is easily accomplished by embedding the concept of virtual centroid into the grasp control to redistribute internal forces. With these concepts, an object can be easily translated, rotated, and manipulated by relocating fingers. The proposed method is verified with experiments.

This paper presents a development of an anthropomorphic robot hand, `KITECH Hand' that has 4 full-actuated fingers. Most robot hands have small size simultaneously many joints as compared with robot manipulators. Components of actuator, gear, and sensors used for building robots are not small and are expensive, and those make it difficult to build a small sized robot hand. Differently from conventional development of robot hands, KITECH hand adopts a RC servo module that is cheap, easily obtainable, and easy to handle. The RC servo module that have been already used for several small sized humanoid can be new solution of building small sized robot hand with many joints. The feasibility of KITECH hand in object manipulation is shown through various experimental results. It is verified that the modified RC servo module is one of effective solutions in the development of a robot hand.

For many years, various local descriptors that are insensitive to geometric changes such as viewpoint, rotation, and scale changes, have been attracting attention due to their promising performance. However, most existing local descriptors including the SIFT (Scale Invariant Feature Transform) are based on luminance information rather than color information thereby resulting in instability to photometric variations such as shadows, highlights, and illumination changes. In this paper, we propose a novel local descriptor, π-SIFT, that are invariant to both geometric and photometric variations. In order to achieve photometric invariance, we adopt photometric quasi-invariant features based on the dichromatic reflection model. The performance of the proposed descriptor is evaluated with SIFT.

A prototype smart home environment for service robots has been constructed in the research building of Korea Institute of Industrial Technology (KITECH) to demonstrate the feasibility of a robot-assisted future home environment. An inexpensive service robot outfitted with a camera, a Radio Frequency Identification (RFID) reader, and a communication module is installed in the building as a future service robot system which is cheap but robust. In our robotic system, the RFID reader gets the rough location data and object information, and then the robot performs the object recognition scheme to get the exact position of the object in order to grasp it. Due to its concise and unambiguous description of the complex media contents, we adopted MPEG-7 visual descriptors for our object recognition system. In this paper, we propose a fast object recognition system for our smart home environment project, on the basis of MPEG-7 visual descriptors including color and texture. Experimental results show that our proposed system works well with good performance in terms of speed and recognition rate. This object recognition system will be incorporated into our mobile robotics platform and a shape descriptor is to be included in the next version of our object recognition system.

Over the past few years, many research groups have attempted to build smart environments. Recently, several groups have been actively conducting research into the construction of smart home environment for service robots to be used as assistants. A home service robot must have are localization, navigation, object recognition, and object handling functionalities. These operations are usually performed by a service robot by itself and the robot can perform the given tasks in a limited environment. In addition, they have shown only limited capabilities in a natural environment. We initiated a smart home environment project, RoboMaidHome, for light-weight service robots to provide reliable services by interacting with the environment through wireless sensor networks. This environment consists of the following three main components: (i) smart objects and smart appliances with sensor network functionality; (ii) a home server that connects smart devices as well as maintains information for reliable services; and (iii) service robots that perform tasks in collaboration with the environment. In this paper, we explain the basic concepts and the architecture of our project and address some key issues related to the project. Finally, we discuss the future directions of our project.

One of the functionalities a service robot should have, to work in a smart environment, is object recognition and handling of objects. Many researchers have attempted to make service robots recognize objects in natural environments but no conventional vision systems can recognize target objects in complex scenes. We built a prototype smart environment in our research building at Korea Institute of Industrial Technology (KITECH) to demonstrate the feasibility that a service robot with few sensors can provide reliable services by interacting with an environment full of smart devices through wireless sensor network communications. In this paper, we address the issues of how to develop an object recognition system for our RoboMaidHome project. Our object recognition system can not only recognize objects with no need of a previous training stage but make the service robot light-weight with minimum hardware and software requirements while working well in a smart home environment. In addition, the matching process for object recognition is simple since only a few image processing techniques are employed. Our object recognition scheme on the basis of MPEG-7 visual descriptors is under development and includes color, texture, and shape. It will also be incorporated into our mobile service robotics system.

A key problem in robotics is the estimation of the location and orientation of objects from surface measurement data. This is termed pose estimation. A fundamental task is the pose estimation of known quadratic surfaces from, possibly noisy, data. A solution for this task facilitates pose estimation for more complex objects. Current algorithms frequently converge to local minima of the performance index and/or pay a high computing cost and/or are sensitive to noise, that are unsuited for online applications because of the intensive computer effort required. The goal is to develop a fast and robust algorithm for pose estimation using range data. Here, pose estimation is carried out using algebraic techniques in a two stage optimization procedure involving least squares estimation, or better the method of instrumental variables, and 3/spl times/3 matrix diagonalizations. The procedure leads to zero pose estimation error in the noise free finite data case, and in the case of infinite data with additive white noise.