Perceiving guaranteed collision-free robot trajectories in unknown and unpredictable environments

The dissertation introduces novel approaches for solving a fundamental problem: detecting a collision-free robot trajectory based on sensing in real-world environments that are mostly unknown and unpredictable, i.e., obstacle geometries and their motions are unknown. Such a collision-free trajectory must provide a guarantee of safe robot motion by accounting for robot motion uncertainty and obstacle motion uncertainty. Further, as simultaneous planning and execution of robot motion is required to navigate in such environments, the collision-free trajectory must be detected in real-time. Two novel concepts: (a) dynamic envelopes and (b) atomic obstacles, are introduced to perceive if a robot at a configuration q, at a future time t, i.e., at a point ? = (q, t) in the robot's configuration-time space (CT space), will be collision-free or not, based on sensor data generated at each sensing moment t, in real-time. A dynamic envelope detects a collision-free region in the CT space in spite of unknown motions of obstacles. Atomic obstacles are used to represent perceived unknown obstacles in the environment at each sensing moment. The robot motion uncertainty is modeled by considering that a robot actually moves in a certain tunnel of a desired trajectory in its CT space. An approach based on dynamic envelopes is presented for detecting if a continuous tunnel of trajectories are guaranteed collision-free in an unpredictable environment, where obstacle motions are unknown. An efficient collision-checker is also developed that can perform fast real-time collision detection between a dynamic envelope and a large number of atomic obstacles in an unknown environment. The effectiveness of these methods is tested for different robots using both simulations and real-world experiments

Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks

Autonomous robots need to interact with unknown, unstructured and changing environments, constantly facing novel challenges. Therefore, continuous online adaptation for lifelong-learning and the need of sample-efficient mechanisms to adapt to changes in the environment, the constraints, the tasks, or the robot itself are crucial. In this work, we propose a novel framework for probabilistic online motion planning with online adaptation based on a bio-inspired stochastic recurrent neural network. By using learning signals which mimic the intrinsic motivation signalcognitive dissonance in addition with a mental replay strategy to intensify experiences, the stochastic recurrent network can learn from few physical interactions and adapts to novel environments in seconds. We evaluate our online planning and adaptation framework on an anthropomorphic KUKA LWR arm. The rapid online adaptation is shown by learning unknown workspace constraints sample-efficiently from few physical interactions while following given way points.Comment: accepted in Neural Network

Interactive form creation: exploring the creation and manipulation of free form through the use of interactive multiple input interface

Most current CAD systems support only the two most common input devices: a mouse and a keyboard that impose a limit to the degree of interaction that a user can have with the system. However, it is not uncommon for users to work together on the same computer during a collaborative task. Beside that, people tend to use both hands to manipulate 3D objects; one hand is used to orient the object while the other hand is used to perform some operation on the object. The same things could be applied to computer modelling in the conceptual phase of the design process. A designer can rotate and position an object with one hand, and manipulate the shape [deform it] with the other hand. Accordingly, the 3D object can be easily and intuitively changed through interactive manipulation of both hands.The research investigates the manipulation and creation of free form geometries through the use of interactive interfaces with multiple input devices. First the creation of the 3D model will be discussed; several different types of models will be illustrated. Furthermore, different tools that allow the user to control the 3D model interactively will be presented. Three experiments were conducted using different interactive interfaces; two bi-manual techniques were compared with the conventional one-handed approach. Finally it will be demonstrated that the use of new and multiple input devices can offer many opportunities for form creation. The problem is that few, if any, systems make it easy for the user or the programmer to use new input devices

The impact of the hospital environment:Understanding the experience of the patient journey

A hospital visit is often an anxious and uncertain event for patients and their relatives. Patients are often concerned about a diagnosis and/or the treatment of their disease in an outpatient or inpatient setting. Knowledge regarding the influence of these settings on patients is essential for facilitating the quality of health care. It is expected that an understanding of the experience of patients will allow designers and decision-makers in hospitals to positively influence the well-being of patients. The aim of this thesis was to gain an improved understanding about a more holistic experience and well-being of patients at specific focal points of the entire patient journey from the arrival, to the diagnosis, and to the actual treatment in a hospital. For example, results showed that patients sometimes experience difficulties in finding their way to an outpatient clinic, that images of nature during a CT scan can reduce anxiety, and that (the opportunity of) interaction with other patients is a pleasant distraction or, on the contrary, an invasion of their own privacy. This thesis emphasizes the relations between the hospital environment and the psychosocial and physical well-being of patients. The results show that it is of great importance to listen carefully to patients’ experiences and needs when designing a hospital as many of the results showed individual differences with patients that emphasize that one size does not fit all. The well-being of patients in future hospitals can be improved by aligning the hospital environment with individual patient characteristics, needs, and preferences

Integrating Vision and Physical Interaction for Discovery, Segmentation and Grasping of Unknown Objects

In dieser Arbeit werden Verfahren der Bildverarbeitung und die Fähigkeit humanoider Roboter, mit ihrer Umgebung physisch zu interagieren, in engem Zusammenspiel eingesetzt, um unbekannte Objekte zu identifizieren, sie vom Hintergrund und anderen Objekten zu trennen, und letztendlich zu greifen. Im Verlauf dieser interaktiven Exploration werden außerdem Eigenschaften des Objektes wie etwa sein Aussehen und seine Form ermittelt

The effect of environment on post surgical overall well-being and pain sensitivity in an animal model

With chronic post surgical pain affecting up to one third of patients undergoing surgeries and the price of treatment being astoundingly high there has been a transition in research to investigate and identify risk factors. Through identification of risk factors new preventative measures can be taken to ensure better surgical outcomes. The role that psychosocial factors can play in the development of chronic post surgical pain has long been recognized yet its mechanisms are still unknown. We aim to investigate how environment can play a direct role in pain perception and sensitivity. We used a Chronic Mild Stress (CMS) paradigm to induce depression in 10 adult male mice, we used 10 control mice who were left in standard opti cages, and 10 enriched mice who were placed in large enrichment cages. CMS mice were exposed to a series of stressors and all mice underwent spared nerve injury surgery. During spared nerve injury the common peroneal and tibial branches of the sciatic nerve were severed while the sural branch was left intact. Overall well-being and pain threshold of mice were tested via Von Frey, Hot Plate, Heat Place Preference, Dynamic Weight Bearing, Hole Board, and Social Interaction. It was found that CMS mice experienced thermal hyperalgesia yet normal thermal threshold sensation. CMS mice also spent less time interacting with novel mice in social interaction, and less amount of time exploring the center of the hole board arena than control or enriched mice. While Von Frey results did not change over the course of the experiment, dynamic weight bearing results indicated spared nerve injury surgery was successful and produced chronic pain. Results indicate that environment plays a role in thermal pain perception and CMS affected overall well being of mice as CMS mice exhibited more timid and anxious behavior

Semi-PROPELLER Compressed Sensing Image Reconstruction with Enhanced Resolution in MRI

Magnetic Resonance Imaging (MRI) reconstruction algorithm using semi-PROPELLER compressed sensing is pre- sented in this paper. It is exhibited that introduced algorithm for estimating data shifts is feasible when super- resolution is applied. The offered approach utilizes compressively sensed MRI PROPELLER sequences and improves MR images spatial resolution in circumstances when highly undersampled k-space trajectories are applied. Compressed Sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were conventionally assumed necessary. Compressed sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were traditionally thought necessary. It is shown that the presented approach improves MR spatial resolution in cases when Compressed Sensing (CS) sequences are used. The application of CS in medical modalities has the potential for significant scan time reductions, with visible benefits for patients and health care economics. These methods emphasize on maximizing image sparsity on known sparse transform do- main and minimizing fidelity. This diagnostic modality struggles with an inherently slow data acquisition process. The use of CS to MRI leads to substantial scan time reductions and visible benefits for patients and economic factors. In this report the objective is to combine Super-Resolution image enhancement algorithm with both PROPELLER sequence and CS framework. All the techniques emphasize on maximizing image sparsity on known sparse transform domain and minimizing fidelity. The motion estimation algorithm being a part of super resolution reconstruction (SRR) estimates shifts for all blades jointly, emphasizing blade-pair correlations that are both strong and more robust to noise.