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.

An investigation of the aspects of occupant behavior required for evacuation modeling

This article examines occupant behavior exhibited during evacuation conditions. This is based on a review of a wide range of published literature concerned with evacuation. Factors influencing evacuation performance can be categorized into four broad areas, namely, configurational, environmental, procedural, and, most importantly, behavioral. The contributory factors associated with each of the four influencing categories are examined in detail and it is suggested that these factors should be represented within evacuation models.

Advanced occupant behavioural features of the building-EXODUS evacuation model

The purpose of this paper is to describe and demonstrate some of the advanced behavioral features currently being developed for the building-EXODUS evacuation model. These advanced features involve the ability to specify roles for particular individuals during the evacuation. With these enhancements to the Behavioral Sub model of building-EXODUS, it is possible to include a number of procedural and behavioral aspects previously ignored in evacuation simulations. These include the behavioral aspect of group bonding, the procedural aspects involved with the role of the fire warden and rescue operations undertaken by the fire services. The importance of these enhancements are discussed and demonstrated through three simple simulations.

Modelling occupant interaction with fire conditions using the buildingEXODUS evacuation model

When evacuating through fire environments, the presence of smoke may not only have a physiological impact on the evacuees but may also lead occupants to adapt their evacuation strategy through the adoption of another exit. This paper attempts to introduce this type of adaptive behaviour within the buildingEXODUS evacuation model through enabling occupants to make decisions concerning the selection of the most viable available exit during an evacuation involving fire. The development of this adaptive behaviour requires the introduction of several new capabilities namely, the representation of the occupants’ familiarity with the structure, the behaviour of an occupant that is engulfed in smoke and the behaviour of an occupant that is faced with a smoke barrier. The appropriateness of the redirection decision is dependent upon behavioural data gathered from real fire incidents (in the UK and USA) that is used to construct the redirection probabilities. The implementation is shown to provide a more complex and arguably more realistic representation of this behaviour than that provided previously.

Investigating the impact of occupant response time on computer simulations of the WTC North Tower evacuation

This work explores the impact of response time distributions on high-rise building evacuation. The analysis utilises response times extracted from printed accounts and interviews of evacuees from the WTC North Tower evacuation of 11 September 2001. Evacuation simulations produced using these “real” response time distributions are compared with simulations produced using instant and engineering response time distributions. Results suggest that while typical engineering approximations to the response time distribution may produce reasonable evacuation times for up to 90% of the building population, using this approach may underestimate total evacuation times by as much as 61%. These observations are applicable to situations involving large high-rise buildings in which travel times are generally expected to be greater than response times