Underwater robotics

As the ocean attracts great attention on environmental issues and resources as well as scientific and military tasks, the need for and use of underwater robotic systems has become more apparent. Underwater robotics represents a fast growing research area and promising industry as advanced technologies in various subsystems develop and potential application areas are explored. Great efforts have been made in developing autonomous underwater vehicles (AUVs) to overcome challenging scientific and engineering problems caused by the unstructured and hazardous ocean environment. With the development of new materials, advanced computing and sensory technology, as well as theoretical advancements, R & D activities in the AUV community have increased. This paper describes current state-of-the art in the area of underwater robotics focusing on some key subsystems.     

Application of Genetic Algorithms for biped robot gait synthesis optimization during walking and going up-stairs

Selecting an appropriate gait can reduce consumed energy by a biped robot. In this paper, a Genetic Algorithm gait synthesis method is proposed, which generates the angle trajectories based on the minimum consumed energy and minimum torque change. The gait synthesis is considered for two cases: walking and going up-stairs. The proposed method can be applied for a wide range of step lengths and step times during walking; or step lengths, stair heights and step times for going up-stairs. The angle trajectories are generated without neglecting the stability of the biped robot. The angle trajectories can be generated for other tasks to be performed by the biped robot, like going down-stairs, overcoming obstacles, etc. In order to verify the effectiveness of the proposed method, the results for minimum consumed energy and minimum torque change are compared. A Radial Basis Function Neural Network is considered for the real-time application. Simulations are realized based upon the parameters of the 'Bonten-Maru I'humanoid robot, which is under development in our laboratory. The evaluation by simulations shows that the proposed method has a good performance.     

Mobile robot tracking of pre-planned paths

A method of mobile robot steering control around pre-planned paths is presented. The system can maneuver accurately at low speeds by deriving control parameters as functions of vehicle velocity. The peak demand on the steering controller is reduced, by distributing steering curvature changes evenly over the extent of a maneuver.     

First results in omni-directional visual servoing

In this paper, we describe a visual servoing system developed as a human-robot interface to drive a mobile robot toward any chosen target. An omni-directional camera is used to get the 360° of field of view and an efficient tracking technique is developed to track the target. The use of the omni-directional geometry eliminates many of the problems common in visual tracking and makes the use of visual servoing a practical alternative for robot-human interaction. The experiments demonstrate that it is an effective and robust way to guide a robot. In particular, the experiments show robustness of the tracker to loss of template, vehicle motion, and change in scale and orientation.     

Gait Recovery in Healthy Subjects: Perturbations to the Knee Motion with a Smart Knee Brace

The Smart Knee Brace (SKB) is designed to provide controlled perturbations to the human knee during walking. A motion capture system records the gait movement before and after these perturbations to assess the human response to the perturbations. A dynamic model of human walking is then used to evaluate the human applied joint torques to hypothesize how the human neuro-muscular system modulates the joint torques as a response to the perturbations caused on the gait. We observe that subjects respond differently to perturbations, but all healthy subjects restore their normal gait in a few subsequent cycles. Our results show that the neuro-muscular response to perturbations can be reasonably well characterized by including the following features in the model: (i) normal gait in the absence of perturbation, (ii) corrective torque at a joint in response to the error at that joint and other joints, and (iii) a characteristic time shift in the response. We believe that there is intuitive justification for each of the components included in the model. Detailed parameters that characterize these components, obtained by data fitting from the response data, are specific to an individual's neuro-muscular response to perturbations in the gait. We believe that these parameters can be used to characterize subjects who are more prone to falling under gait perturbations.     

Behavior coordination in structured environments

Behavior coordination is a notorious problem in mobile robotics. Behaviors are either in competition or collaborating to achieve the goals of a system, which leads to requirements for arbitration and/or fusion of control signals. In most systems the arbitration is specified in terms of 'events' that denote positions or sensory input. The detection of these events allows discrete switching between groups of behaviors. In contrast, the fusion of behaviors is often achieved using potential fields, fuzzy rules or superposition. In most cases, the underlying theoretical foundation is rather weak and the behavior switching results in discrete changes in the overall system dynamics. In this paper, we present a scheme for behavior coordination that is grounded in the dynamical systems approach. The methodology provides a solid theoretical basis for analysis and design of individual behaviors and their coordination. This coordination framework is demonstrated in the context of a domestic robot for fetch-and-carry-type tasks. It is shown here that behavior coordination can be analyzed as an integral part of the design to facilitate smooth transition and fusion between behaviors.     

Biped walking pattern generation by a simple three-dimensional inverted pendulum model

For three-dimensional (3D) walking control of a biped robot we analyze the dynamics of a 3D inverted pendulum in which motion is constrained to move along an arbitrarily defined plane. This analysis leads us to a simple linear dynamics, the Three-Dimensional Linear Inverted Pendulum Mode (3D-LIPM). The geometric nature of the trajectories under the 3D-LIPM and a method for walking pattern generation are discussed. A simulation result of a walking control using a 12-d.o.f. biped robot model is also shown.     

Stability analysis and robust composite controller synthesis for flexible joint robots

In this paper the control of flexible joint manipulators is studied in detail. The model of N-axis flexible joint manipulators is derived and reformulated in the form of singular perturbation theory and an integral manifold is used to separate fast dynamics from slow dynamics. A composite control algorithm is proposed for the flexible joint robots, which consists of two main parts. Fast control, u _f, guarantees that the fast dynamics remains asymptotically stable and the corresponding integral manifold remains invariant. Slow control, u _s, consists of a robust PID designed based on the rigid model and a corrective term designed based on the reduced flexible model. The stability of the fast dynamics and robust stability of the PID scheme are analyzed separately, and finally, the closed-loop system is proved to be uniformly ultimately bounded (UUB) stable by Lyapunov stability analysis. Finally, the effectiveness of the proposed control law is verified through simulations. The simulation results of single- and two-link flexible joint manipulators are compared with the literature. It is shown that the proposed control law ensures robust stability and performance despite the modeling uncertainties.     

Sensor system of a small biped entertainment robot

SDR-4X II is the latest prototype model of a small biped entertainment robot. It is the improved model of SDR-4X. In this paper we report on the sensing system of this robot, which is important and essential for a small biped entertainment robot which will be used in the home environment. One technology is the design of the motion sensing system, i.e. the inclination sensor system and the force sensor system which obtains the inclination of the trunk and the foot with force. Another technology is the real-world sensing system. One aspect is the touch sensing system. The robot is used in a normal home environment, so we should strongly consider the safety aspects for human. Another is the vision sensor system. The configuration and the distance image acquisition are explained. Next is the audio sensor system which obtains the sound and the voice information. The hardware system and the direction recognition are explained. These sensing systems are the key to making the biped robot walking and dynamic motion highly stable, and understanding the real-world around the robot.     

Self-organization of Dynamic Object Features Based on Bidirectional Training

This paper presents a method to self-organize object features that describe object dynamics using bidirectional training. The model is composed of a dynamics learning module and a feature extraction module. Recurrent Neural Network with Parametric Bias (RNNPB) is utilized for the dynamics learning module, learning and self-organizing the sequences of robot and object motions. A hierarchical neural network is linked to the input of RNNPB as the feature extraction module for self-organizing object features that describe the object motions. The two modules are simultaneously trained through bidirectional training using image and motion sequences acquired from the robot's active sensing with objects. Experiments are performed with the robot's pushing motion with a variety of objects to generate sliding, falling over, bouncing and rolling motions. The results have shown that the model is capable of self-organizing object dynamics based on the self-organized features.