Abstract: This paper discusses a strategy by which a robotic hand can use the physical properties of a fabric to pinch the fabric. Pinching may be accomplished by using a wiping motion, during which the movement and deformation of a deformable object occur simultaneously. The wiping motion differs from the displacement of a deformable object. During the wiping motion, there is contact, but no relative movement, between the manipulator and the object, whereas, during displacement, there is both contact and relative movement between the object and the floor. This paper first describes wiping motion and distinguishes wiping slide from wiping deformation by displacement of the internal points of an object. Wiping motion is also shown to be an extended scheme of pushing and sliding of rigid objects. Our strategy for pinching a fabric is accomplished with a combination of wiping deformation and residual deformation of the fabric under unloaded conditions. Using this strategy, a single-armed robotic hand can pinch both surfaces of the fabric without handover motion.
Abstract: Vibration measurement for flexible structures is widely used in various kinds of precision engineering fields. However, it is a challenge to measure vibration in special applications, such as cryogenic, dangerous and magnetic interference. In this paper, a high-precision vibration measurement system based on machine vision is designed. The circle center on the target is employed as the image feature. The circle feature is extracted using the improved algorithm based on gradient Hough transform. Then the image Jacobian matrix is used to compute the vibrations in Cartesian space from the image feature changes. Experiments verify the effectiveness of the proposed methods.
Abstract: The traditional environment maps built by mobile robots include both metric ones and topological ones. These maps are navigation-oriented and not adequate for service robots to interact with or serve human users who normally rely on the conceptual knowledge or semantic contents of the environment. Therefore, the construction of semantic maps becomes necessary for building an effective human-robot interface for service robots. This paper reviews recent research and development in the field of visual-based semantic mapping. The main focus is placed on how to extract semantic information from visual data in terms of feature extraction, object/place recognition and semantic representation methods.
Abstract: The excellent compliance and large range of motion of soft actuators controlled by fluid pressure has lead to strong interest in applying devices of this type for biomimetic and human-robot interaction applications. However, in contrast to soft actuators fabricated from stretchable silicone materials, conventional technologies for position sensing are typically rigid or bulky and are not ideal for integration into soft robotic devices. Therefore, in order to facilitate the use of soft pneumatic actuators in applications where position sensing or closed loop control is required, a soft pneumatic bending actuator with an integrated carbon nanotube position sensor has been developed. The integrated carbon nanotube position sensor presented in this work is flexible and well suited to measuring the large displacements frequently encountered in soft robotics. The sensor is produced by a simple soft lithography process during the fabrication of the soft pneumatic actuator, with a greater than 30% resistance change between the relaxed state and the maximum displacement position. It is anticipated that integrated resistive position sensors using a similar design will be useful in a wide range of soft robotic systems.
Abstract: As societies move towards integration of robots, it is important to study how robots can use their cognition in order to choose effectively their actions in a human environment, and possibly adapt to new contexts. When modelling these contextual data, it is common in social robotics to work with data extracted from human sciences such as sociology, anatomy, or anthropology. These heterogeneous data need to be efficiently used in order to make the robot adapt quickly its actions. In this paper we describe a methodology for the use of heterogeneous and incomplete knowledge, through an algorithm based on naive Bayes classifier. The model was successfully applied to two different experiments of human-robot interaction.
Abstract: This article discusses a control architecture for autonomous sailboat navigation and also presents a sailboat prototype built for experimental validation of the proposed architecture. The main goal is to allow long endurance autonomous missions, such as ocean monitoring. As the system propulsion relies on wind forces instead of motors, sailboat techniques are introduced and discussed, including the needed sensors, actuators and control laws. Mathematical modeling of the sailboat, as well as control strategies developed using PID and fuzzy controllers to control the sail and the rudder are also presented. Furthermore, we also present a study of the hardware architecture that enables the system overall performance to be increased. The sailboat movement can be planned through predetermined geographical way-points provided by a base station. Simulated and experimental results are presented to validate the control architecture, including tests performed on a lake. Underwater robotics can rely on such a platform by using it as a basis vessel, where autonomous charging of unmanned vehicles could be done or else as a relay surface base station for transmitting data.