Place categorization and semantic mapping on a mobile robot

In this paper we focus on the challenging problem of place categorization and semantic mapping on a robot with-out environment-specific training. Motivated by their ongoing success in various visual recognition tasks, we build our system upon a state-of-the-art convolutional network. We overcome its closed-set limitations by complementing the network with a series of one-vs-all classifiers that can learn to recognize new semantic classes online. Prior domain knowledge is incorporated by embedding the classification system into a Bayesian filter framework that also ensures temporal coherence. We evaluate the classification accuracy of the system on a robot that maps a variety of places on our campus in real-time. We show how semantic information can boost robotic object detection performance and how the semantic map can be used to modulate the robot’s behaviour during navigation tasks. The system is made available to the community as a ROS module.

Painehaavapotilaille tehtyjen hoitointerventioiden määrä ja tulokset HYKS:n plastiikkakirurgian klinikassa

Keräsimme ICD-10 koodilla L89 HYKS:n plastiikkakirurgian klinikassa hoidetuista 401:stä potilaasta hoitotiedot vuosilta 2000-2008. Plastiikkakirurgiseen leikkaukseen ja hoidon arvioon päätyneiden potilaiden keski-ikä oli 60,3 (18-97v.). Painehaavan riskitekijät selvitettiin. Yksittäisistä riskitekijöistä yleisimpiä olivat paraplegia ( n=77; 17% ) ja diabetes/ASO tauti ( n=53; 12 % ). Yhteensä painehaavaleikkauksia tehtiin 347 , joista revisioleikkauksia 108 ja varsinaisia sulkuleikkauksia oli 239. Keskimäärin potilaat tarvitsivat 1.7 operaatiota. Leikatuista painehaavoista gradus III- haavoja oli 35,1% ; n= 84 ja gradus IV 25,5% ; n= 61, pinta-ala haavoilla oli keskimäärin 30,5 cm2. Istuinkyhmyjen ja sacrumin painehaavat olivat potilasaineistossamme yleisiä (20% ja 27% operoiduista painehaavoista). Gradus III haavoja leikattiin keskimäärin 1,6 kertaa ja gradus IV haavoja keskimäärin 2,0 kertaa. Postoperatiivisia poliklinikkakäyntejä tarvittiin keskimäärin 2,3, gradus III painehaavapotilailla 2,0 ja gradus IV potilailla 2,6 käyntiä. Leikkausmenetelmistä eri kielekerekonstruktiot olivat selkeästi eniten käytetty leikkausmenetelmä painehaavaleikkauksissa: 58 % rekonstruktioleikkauksista suoritettiin käyttäen jonkinlaista iho- lihaskielekettä. (134 sanaa)

Glowworm-inspired robot swarm for simultaneous taxis towards multiple radiation sources

This paper presents a glowworm metaphor based distributed algorithm that enables a collection of minimalist mobile robots to split into subgroups, exhibit simultaneous taxis-behavior towards, and rendezvous at multiple radiation sources such as nuclear/hazardous chemical spills and fire-origins in a fire calamity. The algorithm is based on a glowworm swarm optimization (GSO) technique that finds multiple optima of multimodal functions. The algorithm is in the same spirit as the ant-colony optimization (ACO) algorithms, but with several significant differences. The agents in the glowworm algorithm carry a luminescence quantity called luciferin along with them. Agents are thought of as glowworms that emit a light whose intensity is proportional to the associated luciferin. The key feature that is responsible for the working of the algorithm is the use of an adaptive local-decision domain, which we use effectively to detect the multiple source locations of interest. The glowworms have a finite sensor range which defines a hard limit on the local-decision domain used to compute their movements. Extensive simulations validate the feasibility of applying the glowworm algorithm to the problem of multiple source localization. We build four wheeled robots called glowworms to conduct our experiments. We use a preliminary experiment to demonstrate the basic behavioral primitives that enable each glowworm to exhibit taxis behavior towards source locations and later demonstrate a sound localization task using a set of four glowworms.

Veneliikenteen määrä Suomessa vuosina 1971 ja 1972

Sammandrag: Båttrafikmängder i Finland under åren 1971 och 1972

Turvemaan männyn (Pinus sylvestris L.) ja kuusen (Picea abies [L.] Karst.) kanto- ja juuripuun ominaisuudet ja asetoniliukoisten uuteaineiden määrä

Tutkimus on osa Metsäklusteri Oy:n Future Biorefinery –tutkimusohjelmaa, jossa kartoitetaan mahdollisuuksia hyödyntää metsäteollisuuden raaka-aineita aiempaa tarkemmin ja uusissa tuotteissa. Tutkimuksen tavoitteena on selvittää männyn (Pinus sylvestris L.) ja kuusen (Picea abies [L.] Karst.) juurten ja kantopuun rakenne ja ominaisuudet. Tutkimuksessa selvitetään löytyykö männyn ja kuusen juurista reaktiopuuta ja määritetään asetoniliukoisten uuteaineiden osuus kantoja juuripuussa. Tutkimusaineistona oli viisi eri-ikäistä mäntyä ja viisi eri-ikäistä kuusta. Juuri- ja kantoaineisto kerättiin Metsäntutkimuslaitoksen toimesta Parkanon seudulta (62.017°N, 23.017°E) hakkuun jälkeen. Maanalaisista juurista otettiin näytteet kolmelta eri etäisyydeltä juurenniskaan nähden. Kummankaan lajin juurista ei löytynyt varsinaista reaktiopuuta, mutta joissakin näytteissä havaittiin lievää reaktiopuuta. Lievää reaktiopuuta löytyi enemmän männyn kuin kuusen juurista, eikä sitä löytynyt lainkaan kaikkein ohuimmista, noin 2 cm paksuisista juurenosista. Männyn kannoissa uuteaineprosentti oli korkeampi kuin kuusen. Männyn juurissa uuteaineprosentti kasvoi edettäessä kohti juuren kärkeä. Kuusella uuteaineprosentti laski aluksi, mutta lähellä juuren kärkeä taas kasvoi. Kuoren uuteainepitoisuus oli molemmilla puulajeilla korkeampi kuin puuaineen. Tutkimusaineisto oli suppea, eikä tutkimuksessa pyritty tilastolliseen yleistettävyyteen. Laajemmasta aineistosta tehdylle tutkimukselle on tarvetta, sillä turvekankailta saatavan puun tarjonta on Suomessa kasvussa, mutta juurten uuteaine- ja reaktiopuututkimuksia on tehty vain kivennäismailta kerätyistä aineistoista.

Composite MR image reconstruction and unaliasing for general trajectories using neural networks

In rapid parallel magnetic resonance imaging, the problem of image reconstruction is challenging. Here, a novel image reconstruction technique for data acquired along any general trajectory in neural network framework, called ``Composite Reconstruction And Unaliasing using Neural Networks'' (CRAUNN), is proposed. CRAUNN is based on the observation that the nature of aliasing remains unchanged whether the undersampled acquisition contains only low frequencies or includes high frequencies too. Here, the transformation needed to reconstruct the alias-free image from the aliased coil images is learnt, using acquisitions consisting of densely sampled low frequencies. Neural networks are made use of as machine learning tools to learn the transformation, in order to obtain the desired alias-free image for actual acquisitions containing sparsely sampled low as well as high frequencies. CRAUNN operates in the image domain and does not require explicit coil sensitivity estimation. It is also independent of the sampling trajectory used, and could be applied to arbitrary trajectories as well. As a pilot trial, the technique is first applied to Cartesian trajectory-sampled data. Experiments performed using radial and spiral trajectories on real and synthetic data, illustrate the performance of the method. The reconstruction errors depend on the acceleration factor as well as the sampling trajectory. It is found that higher acceleration factors can be obtained when radial trajectories are used. Comparisons against existing techniques are presented. CRAUNN has been found to perform on par with the state-of-the-art techniques. Acceleration factors of up to 4, 6 and 4 are achieved in Cartesian, radial and spiral cases, respectively. (C) 2010 Elsevier Inc. All rights reserved.

Dynamical Resolution of Redundancy for Robot Manipulators

A large class of work in the robot manipulator literature deals with the kinematical resolution of redundancy based on the pseudo-inverse of the manipulator Jacobian. In this paper an alternative dynamical approach to redundancy resolution is developed which utilizes the mapping between the actuator torques and the acceleration of the end-effector, at a given dynamic state of the manipulator. The potential advantages of the approach are discussed and an example of a planar 3R manipulator following a circular end-effector trajectory is used to illustrate the proposed approach as well as to compare it with the more well-known approach based on the pseudo-inverse.

An Efficient Random Walk Strategy for Sampling Based Robot Motion Planners

Sampling based planners have been successful in path planning of robots with many degrees of freedom, but still remains ineffective when the configuration space has a narrow passage. We present a new technique based on a random walk strategy to generate samples in narrow regions quickly, thus improving efficiency of Probabilistic Roadmap Planners. The algorithm substantially reduces instances of collision checking and thereby decreases computational time. The method is powerful even for cases where the structure of the narrow passage is not known, thus giving significant improvement over other known methods.

Performance of a class of multi-robot deploy and search strategies based on centroidal voronoi configurations

This article considers a class of deploy and search strategies for multi-robot systems and evaluates their performance. The application framework used is deployment of a system of autonomous mobile robots equipped with required sensors in a search space to gather information. The lack of information about the search space is modelled as an uncertainty density distribution. The agents are deployed to maximise single-step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for sequential deploy and search (SDS) and combined deploy and search (CDS) strategies. Completeness results are provided for both search strategies. The deployment strategy is analysed in the presence of constraints on robot speed and limit on sensor range for the convergence of trajectories with corresponding control laws responsible for the motion of robots. SDS and CDS strategies are compared with standard greedy and random search strategies on the basis of time taken to achieve reduction in the uncertainty density below a desired level. The simulation experiments reveal several important issues related to the dependence of the relative performances of the search strategies on parameters such as the number of robots, speed of robots and their sensor range limits.

A Compact and Compliant External Pipe-Crawling Robot

The focus of this paper is on the practical aspects of design, prototyping, and testing of a compact, compliant external pipe-crawling robot that can inspect a closely spaced bundle of pipes in hazardous environments and areas that are inaccessible to humans. The robot consists of two radially deployable compliant ring actuators that are attached to each other along the longitudinal axis of the pipe by a bidirectional linear actuator. The robot imitates the motion of an inchworm. The novel aspect of the compliant ring actuator is a spring-steel compliant mechanism that converts circumferential motion to radial motion of its multiple gripping pads. Circumferential motion to ring actuators is provided by two shape memory alloy (SMA) wires that are guided by insulating rollers. The design of the compliant mechanism is derived from a radially deployable mechanism. A unique feature of the design is that the compliant mechanism provides the necessary kinematic function within the limited annular space around the pipe and serves as the bias spring for the SMA wires. The robot has a control circuit that sequentially activates the SMA wires and the linear actuator; it also controls the crawling speed. The robot has been fabricated, tested, and automated. Its crawling speed is about 45 mm/min, and the weight is about 150 g. It fits within an annular space of a radial span of 15 mm to crawl on a pipe of 60-mm outer diameter.