7 research outputs found
Position Control of the Single Spherical Wheel Mobile Robot by Using the Fuzzy Sliding Mode Controller
A spherical wheel robot or Ballbotβa robot that balances on an actuated spherical ballβis a new and recent type of robot in the popular area of mobile robotics. This paper focuses on the modeling and control of such a robot. We apply the Lagrangian method to derive the governing dynamic equations of the system. We also describe a novel Fuzzy Sliding Mode Controller (FSMC) implemented to control a spherical wheel mobile robot. The nonlinear nature of the equations makes the controller nontrivial. We compare the performance of four different fuzzy controllers: (a) regulation with one signal, (b) regulation and position control with one signal, (c) regulation and position control with two signals, and (d) FSMC for regulation and position control with two signals. The system is evaluated in a realistic simulation and the robot parameters are chosen based on a LEGO platform, so the designed controllers have the ability to be implemented on real hardware
Impact of UAV Hardware Options on Bridge Inspection Mission Capabilities
Uncrewed Aerial Vehicles (UAV) constitute a rapidly evolving technology field that is becoming more accessible and capable of supplementing, expanding, and even replacing some traditionally manual bridge inspections. Given the classification of the bridge inspection types as initial, routine, in-depth, damage, special, and fracture critical members, specific UAV mission requirements can be developed, and their suitability for UAV application examined. Results of a review of 23 applications of UAVs in bridge inspections indicate that mission sensor and payload needs dictate the UAV configuration and size, resulting in quadcopter configurations being most suitable for visual camera inspections (43% of visual inspections use quadcopters), and hexa- and octocopter configurations being more suitable for higher payload hyperspectral, multispectral, and Light Detection and Ranging (LiDAR) inspections (13%). In addition, the number of motors and size of the aircraft are the primary drivers in the cost of the vehicle. 75% of vehicles rely on GPS for navigation, and none of them are capable of contact inspections. Factors that limit the use of UAVs in bridge inspections include the UAV endurance, the capability of navigation in GPS deprived environments, the stability in confined spaces in close proximity to structural elements, and the cost. Current research trends in UAV technologies address some of these limitations, such as obstacle detection and avoidance methods, autonomous flight path planning and optimization, and UAV hardware optimization for specific mission requirements
Projection Surfaces Detection and Image Correction for Mobile Robots in HRI
Projectors have become a widespread tool to share information in Human-Robot Interaction with large groups of people in a comfortable way. Finding a suitable vertical surface becomes a problem when the projector changes positions when a mobile robot is looking for suitable surfaces to project. Two problems must be addressed to achieve a correct undistorted image: (i) finding the biggest suitable surface free from obstacles and (ii) adapting the output image to correct the distortion due to the angle between the robot and a nonorthogonal surface. We propose a RANSAC-based method that detects a vertical plane inside a point cloud. Then, inside this plane, we apply a rectangle-fitting algorithm over the region in which the projector can work. Finally, the algorithm checks the surface looking for imperfections and occlusions and transforms the original image using a homography matrix to display it over the area detected. The proposed solution can detect projection areas in real-time using a single Kinect camera, which makes it suitable for applications where a robot interacts with other people in unknown environments. Our Projection Surfaces Detector and the Image Correction module allow a mobile robot to find the right surface and display images without deformation, improving its ability to interact with people
Artificial Intelligence and Cognitive Computing
Artificial intelligence (AI) is a subject garnering increasing attention in both academia and the industry today. The understanding is that AI-enhanced methods and techniques create a variety of opportunities related to improving basic and advanced business functions, including production processes, logistics, financial management and others. As this collection demonstrates, AI-enhanced tools and methods tend to offer more precise results in the fields of engineering, financial accounting, tourism, air-pollution management and many more. The objective of this collection is to bring these topics together to offer the reader a useful primer on how AI-enhanced tools and applications can be of use in todayβs world. In the context of the frequently fearful, skeptical and emotion-laden debates on AI and its value added, this volume promotes a positive perspective on AI and its impact on society. AI is a part of a broader ecosystem of sophisticated tools, techniques and technologies, and therefore, it is not immune to developments in that ecosystem. It is thus imperative that inter- and multidisciplinary research on AI and its ecosystem is encouraged. This collection contributes to that
Impact ofΒ Ear Occlusion onΒ In-Ear Sounds Generated byΒ Intra-oral Behaviors
We conducted a case study with one volunteer and a recording setup to detect sounds induced by the actions: jaw clenching, tooth grinding, reading, eating, and drinking. The setup consisted of two in-ear microphones, where the left ear was semi-occluded with a commercially available earpiece and the right ear was occluded with a mouldable silicon ear piece. Investigations in the time and frequency domains demonstrated that for behaviors such as eating, tooth grinding, and reading, sounds could be recorded with both sensors. For jaw clenching, however, occluding the ear with a mouldable piece was necessary to enable its detection. This can be attributed to the fact that the mouldable ear piece sealed the ear canal and isolated it from the environment, resulting in a detectable change in pressure. In conclusion, our work suggests that detecting behaviors such as eating, grinding, reading with a semi-occluded ear is possible, whereas, behaviors such as clenching require the complete occlusion of the ear if the activity should be easily detectable. Nevertheless, the latter approach may limit real-world applicability because it hinders the hearing capabilities.</p
ΠΠ°ΡΡΠ½Π°Ρ ΠΈΠ½ΠΈΡΠΈΠ°ΡΠΈΠ²Π° ΠΈΠ½ΠΎΡΡΡΠ°Π½Π½ΡΡ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² ΠΈ Π°ΡΠΏΠΈΡΠ°Π½ΡΠΎΠ² : ΡΠ±ΠΎΡΠ½ΠΈΠΊ Π΄ΠΎΠΊΠ»Π°Π΄ΠΎΠ² II ΠΠ΅ΠΆΠ΄ΡΠ½Π°ΡΠΎΠ΄Π½ΠΎΠΉ Π½Π°ΡΡΠ½ΠΎ-ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΊΠΎΠ½ΡΠ΅ΡΠ΅Π½ΡΠΈΠΈ, Π’ΠΎΠΌΡΠΊ, 26-28 Π°ΠΏΡΠ΅Π»Ρ 2022 Π³.
Π‘Π±ΠΎΡΠ½ΠΈΠΊ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΠ΅Ρ ΠΈΠ½ΡΠ΅ΡΠ΅Ρ Π΄Π»Ρ ΡΠΏΠ΅ΡΠΈΠ°Π»ΠΈΡΡΠΎΠ² ΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»Π΅ΠΉ Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠΈ, ΠΌΠ΅Ρ
Π°Π½ΠΈΠΊΠΈ, ΡΠ»Π΅ΠΊΡΡΠΎΡΠ΅Ρ
Π½ΠΈΠΊΠΈ, ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΊΠΈ ΠΈ Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠΈΡΡΠ΅ΠΌ, ΡΠΈΠ·ΠΈΠΊΠΈ, Ρ
ΠΈΠΌΠΈΠΈ, Π³Π΅ΠΎΠ»ΠΎΠ³ΠΈΠΈ, Π³ΡΠΌΠ°Π½ΠΈΡΠ°ΡΠ½ΡΡ
Π½Π°ΡΠΊ ΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ