In this paper, an adaptive high gain control is investigated for nonholonomic systems with uncertain control coefficients. By using the high gain technique, it is possible to design a stabilizing controller for such uncertain controlled systems. In addition, the designed adaptive controller is rather simple, since it has only one adaptive adjusting term even though there are a lot of uncertainties in the controlled system. The application of this controller to a nonholonomic wheeled mobile robot is considered as an illustrative example.
This study examined simulator-based methods of illustrating risks to elderly drivers in order to improve their ability to anticipate hazards. Experiments were performed using hypothesized driving programs, in which participants learned the importance of considering other cars' behaviors during lane changes, both their own and those of other drivers. The lane change risks that the elderly drivers were intended to learn to anticipate in their driving were presented using the simulator. The results showed that these presentation methods may be more effective than verbal explanations in helping elderly drivers with reduced metacognitive abilities understand risks. In particular, the most effective method of exposing drivers to the experience of risk promoted the consideration of one's surroundings in scenarios where another car changes lanes. Among the programs that reminded participants of the need to consider the car behind them when changing lanes, the trailing perspective review method was most effective. Based on our findings, this study presents implications that may be useful in developing driving simulator-based educational programs for elderly drivers.
The goal of this paper is to improve tracking performance of a bilateral teleoperation system with communication time delay. The proposed method is a passivity-based PID-type controller. First, using feedback passivation control, the authors make the master and slave robots passive with respect to the new output including position and velocity signals. Secondly, the PI controller for the new output is designed. In the proposed method, position coordination is achieved even with the viscous friction error situation. The stability of the proposed PID teleoperation system and tracking performance are shown via passivity based stability analysis. Finally, several experimental results show the effectiveness of the proposed control methodology for teleoperation systems.
This paper addresses a distributed function calculation in switching topology networks. In particular, a linear iterative strategy is used to perform a general function calculation of the node's initial values. This study shows that if the union graph of the switching networks is connected, the distributed function calculation can be performed. The distributed algorithm allows the nodes in the switching topology network to reach consensus in a finite number of time-steps, which is upper bounded by the size of network and switching period. The distributed function calculation is approached from the perspective of observability theory and treats the iterative strategy as linear dynamic systems. Finally, this work shows that if a jointly connected graph in the switching topology network is structurally observable, then each node obtains enough information to perform an arbitrary function calculation.
Developing autonomous mobile robots that can coexist with human in populated environments is still considered a big challenge. To address this problem the authors propose a novel scheme to assist mobile robots by providing localization information externally. This scheme combines the autonomous navigation and target tracking research fields to arrive at a structured assistance system for autonomous mobile robots. In the proposed scheme, the environment is sensed using a laser range finder and a camera based sensor unit. Using the Rao-Blackwellized particle filter technique, the robots that need assistance are continuously tracked. In contrast with conventional laser range finder based tracking systems, the placement of the sensor is changed to a level above average human height and the mobile robots are modified by attaching a cylindrical pole. The experiments showed the validity of the proposed scheme for simultaneous localization assistance for multiple mobile robots. Two mobile robots were simultaneously navigated in given trajectories using assistance data, successfully.
Design methods of adaptive H∞ formation control of multi-agent systems composed of mobile robots are presented in this paper. The proposed control schemes are derived as solutions of certain H∞ control problems, where estimation errors of tuning parameters and error terms in potential functions are regarded as external disturbances to the process. It is shown that the resulting control systems are robust to uncertain system parameters and that the desirable formations are achieved asymptotically via adaptation schemes.
A pragmatic framework for detecting (identifying the on-off state of) the external force applied to a construction manipulator (front load) by using a hydraulic sensor is proposed. Such a load detecting system requires high accuracy and robustness considering the uncertainty in pressure-based force measurement. The proposed framework first identifies the dominant error force component, including self-weight and driving force, using theoretical and experimental estimation and binarizes the analog cylinder external force. It then evaluates detection conditions to address indeterminate conditions such as stroke-end, singular posture, and impulsive or oscillatory force and redefines three-valued outputs such as on, off, or not determinate (ND). It finally outputs the front load decision by combining all the cylinder decisions to improve robustness through priority analysis. Experiments were conducted using an instrumented hydraulic arm. Results indicate that the proposed framework detects on, off, and ND outputs of the front load more accurately, robustly, and stably in various detection conditions.
A new framework is presented for saliency based analysis of naturally complex scenes. In this framework, the fluctuation of local scale shift and the diversity of subtle chromatic scattering are extracted as the environmental saliency: viewer specific visualization of sign patterns to be associated with landmark objects. Being guided by the probability distribution of the scale shift, the scene image is partitioned into a fractal attractor spanning the roadway area and associated distribution of boundary objects. The chromatic diversity of the scene image is evaluated within a probabilistic color space as the support of a saliency index. The saliency index is applied to the estimate of the invariant measure to capture the sign patterns as fractal attractors within the boundary distribution. Thus, the scale-chromatic aspects of the environmental saliency are articulated into a system of fractal attractors of perceptually equivalence to jointly identify ground-object structure. Through experimental studies, it has been demonstrated that the complexity of decision steps in the detection of landmark objects can be significantly reduced by the saliency based articulation. Adding to it, the perceptual equivalence between the scale- and chromatic-aspects of the environmental saliency is testable via the multi-fractal articulation; to this end, it is sufficient to match the fractal attractors designed in 2D chromatic aspect with 3D landmarks through the projection into 2.5D scale aspect. By this perceptual equivalence, a self-reflective mechanism is induced in the two-aspect representation of the environmental saliency.