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It is important for older and disabled people who live alone to be able to cope with the daily challenges of living at home. In order to support independent living, the Smart Home Care (SHC) concept offers the possibility of providing comfortable control of operational and technical functions using a mobile robot for operating and assisting activities to support independent living for elderly and disabled people. This article presents a unique proposal for the implementation of interoperability between a mobile robot and KNX technology in a home environment within SHC automation to determine the presence of people and occupancy of occupied spaces in SHC using measured operational and technical variables (to determine the quality of the indoor environment), such as temperature, relative humidity, light intensity, and CO2 concentration, and to locate occupancy in SHC spaces using magnetic contacts monitoring the opening/closing of windows and doors by indirectly monitoring occupancy without the use of cameras. In this article, a novel method using nonlinear autoregressive Neural Networks (NN) with exogenous inputs and nonlinear autoregressive is used to predict the CO2 concentration waveform to transmit the information from KNX technology to mobile robots for monitoring and determining the occupancy of people in SHC with better than 98% accuracy.
- Klíčová slova
- KNX technology, Smart Home Care, localization, mobile robot, occupancy, presence,
- MeSH
- lidé MeSH
- oxid uhličitý MeSH
- robotika * metody MeSH
- samostatný způsob života MeSH
- senioři MeSH
- služby domácí péče * MeSH
- technologie MeSH
- Check Tag
- lidé MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- oxid uhličitý MeSH
Planar fiducial markers are commonly used to estimate a pose of a camera relative to the marker. This information can be combined with other sensor data to provide a global or local position estimate of the system in the environment using a state estimator such as the Kalman filter. To achieve accurate estimates, the observation noise covariance matrix must be properly configured to reflect the sensor output's characteristics. However, the observation noise of the pose obtained from planar fiducial markers varies across the measurement range and this fact needs to be taken into account during the sensor fusion to provide a reliable estimate. In this work, we present experimental measurements of the fiducial markers in real and simulation scenarios for 2D pose estimation. Based on these measurements, we propose analytical functions that approximate the variances of pose estimates. We demonstrate the effectiveness of our approach in a 2D robot localisation experiment, where we present a method for estimating covariance model parameters based on user measurements and a technique for fusing pose estimates from multiple markers.
- Klíčová slova
- Kalman filter, observation noise, planar fiducial marker, robot localisation,
- MeSH
- počítačová simulace MeSH
- robotika * MeSH
- zaměřovací značky pro radioterapii * MeSH
- Publikační typ
- časopisecké články MeSH
The review discusses the possibilities of different driving mechanisms and sensors of spherical robots, and a special kind of mobile robots is introduced and discussed. The sensors discussed can expand robots' sensing capabilities which are typically very limited. Most spherical robots have holonomic characteristics and protect the inner environment using a shell. Today, there are a diversity of driving mechanisms. Therefore, this article provides a review of all of them and identifies their basic properties. Accordingly, many spherical robots have only inner sensors for moving, balancing, driving, etc. However, a few of them are also equipped with sensors that can measure environmental properties. Therefore, in this paper, we propose the possibility of using such sensors as cameras, LiDARs, thermocouples, and gas sensors, which can be used for special purposes underground, for example, in mines, underground tunnels, or road tunnels. After combining all components are combined, it is possible to design a special type of spherical robot designed for underground exploration, such as accidents in mines or road tunnels.
- Klíčová slova
- LiDAR, cameras, gas sensors, inertial sensors, mobile robot, special applications, spherical robot, temperature sensors, tunnel applications,
- MeSH
- robotika * MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
A comparison of behavior-based and planning approaches of robot control is presented in this paper. We focus on miniature mobile robotic agents with limited sensory abilities. Two reactive control mechanisms for an agent are considered-a radial basis function neural network trained by evolutionary algorithm and a traditional reinforcement learning algorithm over a finite agent state space. The control architecture based on localization and planning is compared to the former method.
INTRODUCTION: Current developments in contemporary surgery include robotization of laparoscopic abdominal procedures. The author aims to give a contemporary view of the process of transition, both from a point of view of surgery prospects, as well as from a patient's benefit point of view. METHOD: Based on literature data and on the authors' own experience with laparoscopic surgery, the author collects results from available studies, evaluating pros of the laparoscopic procedures compared to the laparotomic ones. Furthermore, he assesses a current situation with a clinical use of the da Vinci robotic system. Development of the surgery field and a therapeutic benefit for a patient are considered the main criteria. RESULTS AND CONCLUSION: Laparoscopic cholecystectomy, fundoplication for a reflux disorder, bariatric procedures and resection of the intestine have become a method of choice or an option listed as a recommended surgical treatment procedure. Laparoscopic appendectomy has restricted indications, laparoscopic reparation of a hernia is recommended for patients, for whom early physical activity is a priority. In order for other procedures to be evaluated, current or new randomized studies need to be completed. There are no significant differences between long-term results of either laparoscopic or laparotomic procedures. Laparoscopic procedures have increased a price of original laparotomic procedures. However, provided better results are evidenced, it is, in most cases, accepted. It is a patient, who benefits from the laparoscopic procedures the most. A surgeon's work ergonomy during laparoscopic procedures with prolonged static body positions may often be worse than during open surgery. Also the procedure itself is, in most cases, more time-demanding. Robot assistence in laparoscopic surgery is a new and fast developing technology of this decade. Currently, its development is in the initial phase. Miniinvasive features are identical with conventional laparoscopic procedures. In order to assess patient's benefits from a robotic system application, the system must be compared with a conventional laparoscopic technique and its results, using randomized studies. The pros of the robotic system include 3D visualization, significantly improved mobility of instruments, better surgeon's ergonomy and elimination of hand shake transition on an instrument. Current disadvantage of the da Vinci robotic system is a high purchase price of the device, costly use due to expensive instrumentation and, so far, not yet confirmed benefits for a patient during abdominal surgery. Pilot projects must be completed to assess the robotic system in abdominal surgery.
- MeSH
- laparoskopie * metody MeSH
- lidé MeSH
- robotika * metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- anglický abstrakt MeSH
- časopisecké články MeSH
- přehledy MeSH
Mobile robots are endeavoring toward full autonomy. To that end, wheeled mobile robots have to function under non-holonomic constraints and uncertainty derived by feedback sensors and/or internal dynamics. Speed control is one of the main and challenging objectives in the endeavor for efficient autonomous collision-free navigation. This paper proposes an intelligent technique for speed control of a wheeled mobile robot using a combination of fuzzy logic and supervised machine learning (SML). The technique is appropriate for flexible leader-follower formation control on straight paths where a follower robot maintains a safely varying distance from a leader robot. A fuzzy controller specifies the ultimate distance of the follower to the leader using the measurements obtained from two ultrasonic sensors. An SML algorithm estimates a proper speed for the follower based on the ultimate distance. Simulations demonstrated that the proposed technique appropriately adjusts the follower robot's speed to maintain a flexible formation with the leader robot.
- Klíčová slova
- autonomous robot, fuzzy system, intelligent technique, speed control, supervised machine learning,
- Publikační typ
- časopisecké články MeSH
In this study, we address generalized autonomous mobile robot exploration of unknown environments where a robotic agent learns a traversability model and builds a spatial model of the environment. The agent can benefit from the model learned online in distinguishing what terrains are easy to traverse and which should be avoided. The proposed solution enables the learning of multiple traversability models, each associated with a particular locomotion gait, a walking pattern of a multi-legged walking robot. We propose to address the simultaneous learning of the environment and traversability models by a decoupled approach. Thus, navigation waypoints are generated using the current spatial and traversability models to gain the information necessary to improve the particular model during the robot's motion in the environment. From the set of possible waypoints, the decision on where to navigate next is made based on the solution of the generalized traveling salesman problem that allows taking into account a planning horizon longer than a single myopic decision. The proposed approach has been verified in simulated scenarios and experimental deployments with a real hexapod walking robot with two locomotion gaits, suitable for different terrains. Based on the achieved results, the proposed method exploits the online learned traversability models and further supports the selection of the most appropriate locomotion gait for the particular terrain types.
- Klíčová slova
- active learning, locomotion gait, mobile robot exploration, multi-legged robot, traversability,
- Publikační typ
- časopisecké články MeSH
Robot-assisted training has been widely used in rehabilitation programs, but no significant clinical evidence about its use in productive working-age cardiac patients was demonstrated. Thus, we hypothesized that early applied robot-assisted physiotherapy might provide additional treatment benefits in the rehabilitation of post-myocardial infarction (MI) patients. A total of 92 (50 men, 42 women) hospitalized post-MI patients with the age of 60.9 ± 2.32 participated in the research. An early intensive physiotherapy program (7×/week, 2×/day) was applied for each patient with an average time of 45 min per session. Patients were consecutively assigned to Experimental group (EG) and Control group (CG). Then, 20 min of robot-assisted training by Motomed letto 2 or Thera-Trainer tigo was included in all EG physiotherapy sessions. The Functional Independence Measures (FIM) score at the admission and after 14 days of rehabilitation was used for an assessment. When analyzing time * group effect by repeated-measures ANOVA, we reported that EG showed a higher effect in ADL (p = 0.00), and Motor indicators (p = 0.00). There was no statistically significant effect reported in the Social indicator (p = 0.35). Early rehabilitation programs for post-MI patients might be enhanced by robotic tools, such as THERA-Trainer tigo, and Motomed letto 2. The improvement was particularly noticeable in mobility and ADLs.
- Klíčová slova
- FIM score, first phase cardiac physiotherapy, myocardial infarction, robot-assisted therapy,
- Publikační typ
- časopisecké články MeSH
In the last forty years, the field of medicine has experienced dramatic shifts in technology-enhanced surgical procedures - from its initial use in 1985 for neurosurgical biopsies to current implementation of systems such as magnetic-guided catheters for endovascular procedures. Systems such as the Niobe Magnetic Navigation system and CorPath GRX have allowed for utilization of a fully integrated surgical robotic systems for perioperative manipulation, as well as tele-controlled manipulation systems for telemedicine. These robotic systems hold tremendous potential for future implementation in cerebrovascular procedures, but lack of relevant clinical experience and uncharted ethical and legal territory for real-life tele-robotics have stalled their adoption for neurovascular surgery, and might present significant challenges for future development and widespread implementation. Yet, the promise that these technologies hold for dramatically improving the quality and accessibility of cerebrovascular procedures such as thrombectomy for acute stroke, drives the research and development of surgical robotics. These technologies, coupled with artificial intelligence (AI) capabilities such as machine learning, deep-learning, and outcome-based analyses and modifications, have the capability to uncover new dimensions within the realm of cerebrovascular surgery.
- Klíčová slova
- Artificial intelligence, Cerebrovascular, Endovascular, Robotic surgery, Tele-surgery, Telerobotics,
- MeSH
- cévní mozková příhoda chirurgie MeSH
- endovaskulární výkony přístrojové vybavení trendy MeSH
- lidé MeSH
- roboticky asistované výkony metody trendy MeSH
- telemedicína přístrojové vybavení metody trendy MeSH
- umělá inteligence trendy MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
Visual teach and repeat navigation (VT&R) is popular in robotics thanks to its simplicity and versatility. It enables mobile robots equipped with a camera to traverse learned paths without the need to create globally consistent metric maps. Although teach and repeat frameworks have been reported to be relatively robust to changing environments, they still struggle with day-to-night and seasonal changes. This paper aims to find the horizontal displacement between prerecorded and currently perceived images required to steer a robot towards the previously traversed path. We employ a fully convolutional neural network to obtain dense representations of the images that are robust to changes in the environment and variations in illumination. The proposed model achieves state-of-the-art performance on multiple datasets with seasonal and day/night variations. In addition, our experiments show that it is possible to use the model to generate additional training examples that can be used to further improve the original model's robustness. We also conducted a real-world experiment on a mobile robot to demonstrate the suitability of our method for VT&R.
- Klíčová slova
- contrastive learning, image representations, long-term autonomy, machine learning, visual teach and repeat navigation,
- MeSH
- neuronové sítě * MeSH
- robotika * metody MeSH
- Publikační typ
- časopisecké články MeSH
