Theoretical and experimental research on time-optimal trajectory planning and control of industrial robots

提出了一种用于工业机器人时间最优轨迹规划及轨迹控制的新方法，它可以确保在关节位移、速度、加速度以及二阶加速度边界值的约束下，机器人手部沿笛卡尔空间中规定路径运动的时间阳短。在这种方法中，所规划的关节轨迹都采用二次多项式加余弦函数的形式，不仅可以保证各关节运动的位移、速度 、加速度连续而且还可以保证各关节运动的二阶加速度连续。采用这种方法，既可以提高机器人的工作效率又可以延长机器人的工作寿命以PUMA560机器人为对象进行了计算机仿真和机器人实验，结果表明这种方法是正确的有效的。它为工业机器人在非线性运动学约束条件下的时间最优轨迹规划及控制问题提供了一种较好的解决方案。

Trajectory Mapping ("TM''): A New Non-Metric Scaling Technique

Trajectory Mapping "TM'' is a new scaling technique designed to recover the parameterizations, axes, and paths used to traverse a feature space. Unlike Multidimensional Scaling (MDS), there is no assumption that the space is homogenous or metric. Although some metric ordering information is obtained with TM, the main output is the feature parameterizations that partition the given domain of object samples into different categories. Following an introductory example, the technique is further illustrated using first a set of colors and then a collection of textures taken from Brodatz (1966).

Improved Tracking of Multiple Humans with Trajectory Prediction and Occlusion Modeling

A combined 2D, 3D approach is presented that allows for robust tracking of moving bodies in a given environment as observed via a single, uncalibrated video camera. Tracking is robust even in the presence of occlusions. Low-level features are often insufficient for detection, segmentation, and tracking of non-rigid moving objects. Therefore, an improved mechanism is proposed that combines low-level (image processing) and mid-level (recursive trajectory estimation) information obtained during the tracking process. The resulting system can segment and maintain the tracking of moving objects before, during, and after occlusion. At each frame, the system also extracts a stabilized coordinate frame of the moving objects. This stabilized frame is used to resize and resample the moving blob so that it can be used as input to motion recognition modules. The approach enables robust tracking without constraining the system to know the shape of the objects being tracked beforehand; although, some assumptions are made about the characteristics of the shape of the objects, and how they evolve with time. Experiments in tracking moving people are described.

3D Trajectory Recovery for Tracking Multiple Objects and Trajectory Guided Recognition of Actions

A mechanism is proposed that integrates low-level (image processing), mid-level (recursive 3D trajectory estimation), and high-level (action recognition) processes. It is assumed that the system observes multiple moving objects via a single, uncalibrated video camera. A novel extended Kalman filter formulation is used in estimating the relative 3D motion trajectories up to a scale factor. The recursive estimation process provides a prediction and error measure that is exploited in higher-level stages of action recognition. Conversely, higher-level mechanisms provide feedback that allows the system to reliably segment and maintain the tracking of moving objects before, during, and after occlusion. The 3D trajectory, occlusion, and segmentation information are utilized in extracting stabilized views of the moving object. Trajectory-guided recognition (TGR) is proposed as a new and efficient method for adaptive classification of action. The TGR approach is demonstrated using "motion history images" that are then recognized via a mixture of Gaussian classifier. The system was tested in recognizing various dynamic human outdoor activities; e.g., running, walking, roller blading, and cycling. Experiments with synthetic data sets are used to evaluate stability of the trajectory estimator with respect to noise.

Trajectory Guided Tracking and Recognition of Actions

A combined 2D, 3D approach is presented that allows for robust tracking of moving people and recognition of actions. It is assumed that the system observes multiple moving objects via a single, uncalibrated video camera. Low-level features are often insufficient for detection, segmentation, and tracking of non-rigid moving objects. Therefore, an improved mechanism is proposed that integrates low-level (image processing), mid-level (recursive 3D trajectory estimation), and high-level (action recognition) processes. A novel extended Kalman filter formulation is used in estimating the relative 3D motion trajectories up to a scale factor. The recursive estimation process provides a prediction and error measure that is exploited in higher-level stages of action recognition. Conversely, higher-level mechanisms provide feedback that allows the system to reliably segment and maintain the tracking of moving objects before, during, and after occlusion. The 3D trajectory, occlusion, and segmentation information are utilized in extracting stabilized views of the moving object that are then used as input to action recognition modules. Trajectory-guided recognition (TGR) is proposed as a new and efficient method for adaptive classification of action. The TGR approach is demonstrated using "motion history images" that are then recognized via a mixture-of-Gaussians classifier. The system was tested in recognizing various dynamic human outdoor activities: running, walking, roller blading, and cycling. Experiments with real and synthetic data sets are used to evaluate stability of the trajectory estimator with respect to noise.

An exploration through interview and drawings of the experiences of patients diagnosed with oral cancer across their cancer trajectory

Background: The treatment of oral cancer is complex and lengthy. Curative treatment implies a combination of surgery, radiotherapy and chemotherapy. The main goal of treatment is to guarantee long-term tumour free survival with as little functional and cosmetic damage. Despite progress in developing these strategies, cancers of the oral cavity continue to have high mortality rates that have not improved dramatically over the past ten years. Aim: The aim of this study was to uniquely explore the dynamic changes in the physical, psychological, social and existential experiences of newly diagnosed patients with oral cancer at two points across their cancer illness trajectory i.e. at the time of diagnosis and at the end of treatment. Methodology: A qualitative prospective longitudinal design was employed. Non-probability purposive sampling allowed the recruitment of 10 participants. The principal data collection method used was a digital audio taped semi-structured interview along with drawings produced by the participants. Analysis: Data was analysed using latent content analyses. Summary: Three ‘dynamic’ themes, physical, psychosocial and existential experiences were revealed that interact and influence each other in a complex and compound whole. These experiences are present at different degrees and throughout the entire trajectory of care. Patients have a number of specific concerns and challenges that cannot be compartmentalised into unitary or discrete aspects of their daily lives. Conclusion & Implications: An understanding of the patient’s experience of their illness at all stages of the disease trajectory, is essential to inform service providers’ decision making if the delivery of care is to be client centred. Dynamic and fluctuating changes in the patient’s personal experience of the cancer journey require dynamic, energetic and timely input from health care professionals.

Using idiothetic cues to swim a path with a fixed trajectory and distance: Necessary involvement of the hippocampus but not the retrosplenial cortex.

Rats rapidly learned to find a submerged platform in a water maze at a constant distance and angle from the start point, which changed on every trial. The rats performed accurately in the light and dark, but prior rotation disrupted the latter condition. The rats were then retested after receiving cytotoxic hippocampal or retrosplenial cortex lesions. Retrosplenial lesions had no apparent effect in either the light or dark. Hippocampal lesions impaired performance in both conditions but spared the ability to locate a platform placed in the center of the pool. A hippocampal deficit emerged when this pool-center task was run in the dark. The spatial effects of hippocampal damage extend beyond allocentric tasks to include aspects of idiothetic guidance.

Interval timing and trajectory in unequal amplitude movements

The Wing-Kristofferson (WK) model of movement timing emphasises the separation of central timer and motor processes. Several studies of repetitive timing have shown that increase in variability at longer intervals is attributable to timer processes; however, relatively little is known about the way motor aspects of timing are affected by task movement constraints. In the present study, we examined timing variability in finger tapping with differences in interval to assess central timer effects, and with differences in movement amplitude to assess motor implementation effects. Then, we investigated whether effects of motor timing observed at the point of response (flexion offset/tap) are also evident in extension, which would suggest that both phases are subject to timing control. Eleven participants performed bimanual simultaneous tapping, at two target intervals (400, 600 ms) with the index finger of each hand performing movements of equal (3 or 6 cm) or unequal amplitude (left hand 3, right hand 6 cm and vice versa). As expected, timer variability increased with the mean interval but showed only small, non-systematic effects with changes in movement amplitude. Motor implementation variability was greater in unequal amplitude conditions. The same pattern of motor variability was observed both at flexion and extension phases of movement. These results suggest that intervals are generated by a central timer, triggering a series of events at the motor output level including flexion and the following extension, which are explicitly represented in the timing system.

Timing and trajectory in rhythm production

The Wing-Kristofferson movement timing model (A. M. Wing & A. B. Kristofferson, 1973a, 1973b) distinguishes central timer and motor implementation processes. Previous studies have shown that increases in interresponse interval (IRI) variability with mean IRI are due to central timer processes, not motor implementation. The authors examine whether this is true with IRI duration changes in binary rhythm production. Ten participants provided IRI and movement data in bimanual synchronous tapping under equal (isochronous) and alternating (rhythm) interval conditions. Movement trajectory changes were observed with IRI duration (300, 500, or 833 ms) and for 500-ms IRIs produced in rhythm contexts (300/500 ms, 500/833 ms). However, application of the Wing-Kristofferson model showed that duration and context effects on IRI variability were attributable largely to timer processes with relatively little effect on motor processes.

Trajectory Control of Electro Hydraulic Excavator using Fuzzy Self Tuning Algorithm with Neural Network

This paper presents the trajectory control of a 2DOF mini electro-hydraulic excavator by using fuzzy self tuning with neural network algorithm. First, the mathematical model is derived for the 2DOF mini electro-hydraulic excavator. The fuzzy PID and fuzzy self tuning with neural network are designed for circle trajectory following. Its two links are driven by an electric motor controlled pump system. The experimental results demonstrated that the proposed controllers have better control performance than the conventional controller.