Designing the Learning Goal Space for Human Toward Acquiring a Creative Learning Skill

This chapter presents the way to design a learning support system toward acquiring a creative skill on learning. There are two research goals. One is to establish designing the creative learning task. The other is to make clear the human sense of creativity. As the background of this research, the jobs with high creativity or social skills will remain in the future. However, acquiring human's creativity is too difficult for computers. To solve this problem, the authors focus on the way to utilize higher creativity of human than that of computers. The main method is the visualization of learning traces to support awareness for creativity on the learning. The authors conducted the preliminary learning experiment with three human subjects. After that, the questionnaire and the hearing investigation were conducted. As the future work, the authors are planning to conduct an updated version of the experiment.

A Real-Time Compressive Tracking System for Amphibious Spherical Robots

Given the special working environments and application functions of the amphibious robot, an improved RGB-D visual tracking algorithm with dual trackers is proposed and implemented in this chapter. Compressive tracking (CT) was selected as the basis of the proposed algorithm to process colour images from a RGB-D camera, and a Kalman filter with a second-order motion model was added to the CT tracker to predict the state of the target, select candidate patches or samples, and reinforce the tracker's robustness to high-speed moving targets. In addition, a variance ratio features shift (VR-V) tracker with a Kalman prediction mechanism was adopted to process depth images from a RGB-D camera. A visible and infrared fusion mechanism or feedback strategy is introduced in the proposed algorithm to enhance its adaptability and robustness. To evaluate the effectiveness of the algorithm, Microsoft Kinect, which is a combination of colour and depth cameras, was adopted for use in a prototype of the robotic tracking system.

Modeling a Predictive Control of Human Locomotion Based on the Dynamic Behavior

This chapter presents the development of a lower limb orthosis based on the continuous dynamic behavior and on the events presented on the human locomotion, when the legs alternate between different functions. A computational model was developed to approach the different functioning models related to the bipedal anthropomorphic gait. Lagrange modeling was used for events modeling the non-holonomic dynamics of the system. This chapter combines the comparison of the use of the predictive control based on dynamical study and the decoupling of the dynamical model, with auxiliary parallelograms, for locating the center of mass of the mechanism using springs in order to achieve the balancing of each leg. Virtual model was implemented and its kinematic and dynamic motion analyzed through simulation of an exoskeleton, aimed at lower limbs, for training and rehabilitation of the human gait, in which the dynamic model of anthropomorphic mechanism and predictive control architecture with robust control is already developed.

Bio-Inspired Snake Robots

This chapter concerns modelling and control of snake robots. Specifically, the authors' main goal is introducing some of the fundamental design, modelling, and control approaches introduced for efficient snake robot locomotion in cluttered environments. This is a critical topic because, unlike locomotion in flat surfaces, where pre-specified gait equations can be employed, for locomotion in unstructured environment more sophisticated control approaches should be used to achieve intelligent and efficient mobility. To reach this goal, shape-based modelling approaches and a number of available control schemes for operation in unknown environments are presented, which hopefully motivates more scholars to start working on snake robots. Some ideas about future research plans are also proposed, which can be helpful for fabricating a snake robot equipped with the necessary features for operation in a real-world environment.

The “Arm” Line of Devices for Neurological Rehabilitation

In the modern scenario of neurological rehabilitation, which requires affordable solutions oriented toward promoting home training, the Institute of Industrial Technologies and Automation (ITIA) of the Italian National Research Council (CNR) developed a line of prototypal devices for the rehabilitation of the upper limb, called “Arm.” Arm devices were conceived to promote rehabilitation at affordable prices by capturing all the main features of the state-of-the-art devices. In fact, Arm devices focus on the main features requested by a robot therapist: mechanical adaptation to the patient, ranging from passive motion to high transparency, assist-as-needed and resistive modalities; proper use of sensors for performance monitoring; easy-to-use, modular, and adaptable design. These desirable features are combined with low-cost, additive manufacturing procedures, with the purpose of meeting the requirements coming from research on neuro-motor rehabilitation and motor control and coupling them with the recent breakthrough innovations in design and manufacturing.

Hybrid Exoskeletons for Upper Limb Stroke Rehabilitation

Hybrid exoskeletons are a recent development, combining electrically controlled actuation with functional electrical stimulation, which potentially offers great benefits for muscular rehabilitation. This chapter presents a review on the state of the art of upper-limb hybrid exoskeletons with a particular focus on stroke rehabilitation. The current needs of the stroke rehabilitation field are discussed and the ability of hybrid exoskeletons to provide a solution to some of the gaps in this field is explored. Due to the early stage of development which most hybrid exoskeletons are in, little research has yet been done in control methods used for them. In particular, more investigation is needed with regards to the potential benefit of hybrid exoskeletons as a patient-monitoring and rehabilitation assist-as-need tool.

Self-Powered Height Sensor With ZigBee Networks for Intelligent Systems

With the development of micro-electro-mechanical systems (MEMS), wireless communication technology, and embedded systems, wireless sensor network (WSN) has been a focus for research among various fields. Wireless sensor technology inspires many innovations for industrial applications and medical robots, and breaks many limitations and inconvenience for such sensing devices. A self-powered height sensing system with ZigBee technology is presented. It specifically targets to replace an original wired system with an integrated wireless sensor that is comprised of all necessary parts: sensing module, processing module, RF transceiver, and power supply. First, the authors present the system framework design including the layout of a wireless sensor node based on ZigBee. Second, with the vibration environment, a self-powered generator was developed through the comparison between piezoelectric and electromagnetic generation. Then several experiments are conducted to test and analyze the feasibility of the whole system. Finally, a future upgraded design is proposed to improve system performance.

Discrimination of Dual-Arm Motions Using a Joint Posterior Probability Neural Network for Human-Robot Interfaces

This chapter describes a novel dual-arm motion discrimination method that combines posterior probabilities estimated independently for left and right arm movements, and its application to control a robotic manipulator. The proposed method estimates the posterior probability of each single-arm motion through learning using recurrent probabilistic neural networks. The posterior probabilities output from the networks are then combined based on motion dependency between arms, making it possible to calculate a joint posterior probability of dual-arm motions. With this method, all the dual-arm motions consisting of each single-arm motion can be discriminated through leaning of single-arm motions only. In the experiments performed, the proposed method was applied to the discrimination of up to 50 dual-arm motions. The results showed that the method enables relatively high discrimination performance. In addition, the possibility of applying the proposed method for a human-robot interface was confirmed through operation experiments for the robotic manipulator using dual-arm motions.

Kinodynamic Motion Planning for a Two-Wheel-Drive Mobile Robot

Since a nonholonomic system such as a robot with two independent driving wheels includes complicated nonlinear terms generally, it is hard to realize a stable and tractable controller design. However, about a dynamic control method for the motion planning, it is guaranteed that a nonholonomic-controlled object can always be converged to an arbitrary point using a control method based on an invariant manifold. Based on it, the method called “kinodynamic motion planning” was proposed to converge the states of the two-wheeled mobile robot to the arbitrary target position while avoiding obstacles by combining the control based on the invariant manifold and the HPF. In this chapter, how to combine the invariant manifold control and the concept of the HPF is explained in detail, and the usefulness of the proposed approach is verified through some simulations.

Brachytherapy Needle Steering Guidance Using Image Overlay

This chapter presents a physical simulator for needle steering in brachytherapy. As the user inserts the needle in a phantom tissue, images of the needle and prostate shape reconstructed from 2D transverse ultrasound images are displayed online in a semi-transparent mirror. During insertion, the user sees the images as if they were floating inside the phantom accounting for scale and orientation. The ultrasound images of the needle are combined with a needle-tissue interaction model that predicts the needle deflection further along the insertion process. The necessary manoeuvres that bring the needle towards its intended target location are displayed to the user along with the actual needle location. This platform allows the user to test different manual and robotic-assisted needle steering techniques. Reported experimental results confirm the accuracy of the system in reconstructing and overlaying images onto the phantom.