A large-stroke rapid motion controller for servo applications with speed and control constraints

Large-stroke rapid motion is required in many industrial servo systems (e.g. pick-and-place applications), on which constraints of control input and motion speed are usually imposed. This paper presents a hybrid control scheme for large-stroke rapid motion in such systems. The controller resorts to the time-optimal control (TOC) for maximum acceleration initially and then switches into a linear control law to achieve smooth settling. A speed regulation stage is inserted in the tracking process to prevent violating the speed constraint. To tackle the unmeasured speed and unknown disturbance, an extended state observer (ESO) can be included in the controller. The controller is applied to a permanent magnet synchronous motor (PMSM) servo system for large-stroke position regulation. Digital simulation via MATLAB is conducted first, followed by an experimental verification using a TMS320F28335 board. The results confirm that the proposed controller can track a wide range of target references with desirable performance under speed constraint and load disturbance and has a competitive advantage over the popular active disturbance-rejection control (ADRC) scheme.

Target dynamic grasping during mobile robot movement based on learning methods

Purpose One of the development trends of robots is to enable robots to have the ability of anthropomorphic manipulation. Grasping is the first step of manipulation. For mobile manipulator robots, grasping a target during the movement process is extremely challenging, which requires the robots to make rapid motion planning for arms under uncertain dynamic disturbances. However, there are many situations require robots to grasp a target quickly while they move, such as emergency rescue. The purpose of this paper is to propose a method for target dynamic grasping during the movement of a robot. Design/methodology/approach An off-line learning from demonstrations method is applied to learn a basic reach model for arm and a motion model for fingers. An on-line dynamic adjustment method of arm speed for active and passive grasping mode is designed. Findings The experimental results of the robot movement on flat, slope and speed bumps ground show that the proposed method can effectively solve the problem of fast planning under uncertain disturbances caused by robot movement. The method performs well in the task of target dynamic grasping during the robot movement. Originality/value The main contribution of this paper is to propose a method to solve the problem of rapid motion planning of the robot arm under uncertain disturbances while the robot is grasping a target in the process of robot movement. The proposed method significantly improves the grasping efficiency of the robot in emergency situations. Experimental results show that the proposed method can effectively solve the problem.

Rapid Motion Control and Design of a Tricopter Style Hovering Ground Robot

An analysis of the design and manufacture of a tricopter style hovercraft is realized in detail, along with the parameters for determining the geometry due to power requirements. The aircraft is constructed with three ducted fans in the vertical orientation, denoting the layout of the classic tricopter frame. The purpose of this study is to establish a design of a ground vehicle capable of multi-terrain navigation. A simplified skirt solution is presented for the aircushion. The model is robust enough for rough terrain and sufficient for maintaining the cushion pressure that enables the ground effect to work towards a higher efficiency. The design process for the model consists of the use of CAD to layout and simulate all components. The efficiency and battery life of the vehicle is compared to the tricopter and a flight test verifies its capability to follow a given path.

Micropools of reliable area MT neurons explain rapid motion detection

Many models of perceptually based decisions postulate that actions are initiated when accumulated sensory signals reach a threshold level of activity. These models have received considerable neurophysiological support from recordings of individual neurons while animals are engaged in motion discrimination tasks. These experiments have found that the activity of neurons in a particular visual area strongly associated with motion processing (MT), when pooled over hundreds of milliseconds, is sufficient to explain behavioral timing and performance. However, this level of pooling may be problematic for urgent perceptual decisions in which rapid detection dictates temporally precise integration. In this paper, we explore the physiological basis of one such task in which macaques detected brief (~70 ms) transients of coherent motion within ~240 ms. We find that a simple linear summation model based on realistic stimulus responses of as few as 40 correlated neurons can predict the reliability and timing of rapid motion detection. The model naturally reproduces a distinctive physiological relationship observed in rapid detection tasks in which the individual neurons with the most reliable stimulus responses are also the most predictive of impending behavioral choices. Remarkably, we observed this relationship across our simulated neuronal populations even when all neurons within the pool were weighted equally with respect to readout. These results demonstrate that small numbers of reliable sensory neurons can dominate perceptual judgments without any explicit reliability based weighting and are sufficient to explain the accuracy, latency, and temporal precision of rapid detection. NEW & NOTEWORTHY Computational and psychophysical models suggest that performance in many perceptual tasks may be based on the preferential sampling of reliable neurons. Recent studies of MT neurons during rapid motion detection, in which only those neurons with the most reliable sensory responses were strongly predictive of the animals’ decisions, seemingly support this notion. Here we show that a simple threshold model without explicit reliability biases can explain both the behavioral accuracy and precision of these detections and the distribution of sensory- and choice-related signals across neurons.

Video Observation of Perseids meteor shower 2016 from Egypt

The results of single television observations of Perseid meteor shower in 2016 are presented. The Perseid shower occurs from 17 July to 24 August, peaking on or around August 12 every year. In 2016, the peak of the Perseids was Night of Aug 11 to the morning of Aug 12. The meteor video observations in Egypt are carried out at The National Researcher Institute of Astronomy and Geophysics (NRIAG). The system consists of TV - cameras Watec -902H Ultimate with the lens DV10x8SA-1 (8-80 mm (10x)) capable of recording the rapid motion of meteors entering the Earth atmosphere.