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检索条件"任意字段=3rd International Workshop on Sensor Based Intelligent Robots"

共 404 条记录，以下是1-10 订阅

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Development of an Adaptive Smart Toy with Emotional Feedback 3

Development of an Adaptive Smart Toy with Emotional Feedback

引用

3rd international Conference on intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Mohandas, Gayathri Sanay Santh, V. Padmakumar, Keshav Thangam, S. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

Traditional toys often do not adapt to the emotional and physical needs of children, particularly those who may have limited verbal communication abilities. The project’s goal is to create a smart toy that is adaptive and can communicate with a child by using nonverbal signs to express his or her physical and emotional states. There are sensors like accelerometers to detect movement, a gesture sensor indicating light intensity, a buzzer sensor to produce sound, and an IR sensor to detect the child’s hand when the child is near the toy. All these components will help the user to get in-time feedback with a set of visual indicators (LEDs) and tactile feedback in the form of vibration motors. This smart toy seeks to improve the experience of play and developmental support for children by being more responsive and engaging with individual needs. © 2025 IEEE.

关键词： intelligent robots

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Advancements in AI-Powered Robotic Cleaning Systems: Autonomous Path Planning, Predictive Maintenance, and Cleanliness Assessment Frameworks

Advancements in AI-Powered Robotic Cleaning Systems: Autonom...

引用

intelligent Data Communication Technologies and Internet of Things (IDCIoT), international Conference on

作者： Jones Sarah A Nandhakumar D Atchitha Magesh Kumar S Pavithra Department of Computer Science and Engineering Chennai Institute of Technology Chennai Tamilnadu India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

Artificial Intelligence (AI) is transforming robotic cleaning systems to be more efficient, safe, and adapt in various environments, including public spaces and industrial facilities. The novelty of these systems is the use of advanced sensing and deep learning to identify areas that need cleaning, plan paths, and save resources all while meeting high cleanliness standards required in sensitive areas like hospitals and pharmaceutical facilities. The objective is how recent developments in path planning, dirt detection, and predictive maintenance improve these systems, which reduce costs and perform without human supervision. Though these systems work well, challenges remain in deciding on cleaning paths for complex spaces, correctly detecting various types of dirt, adapting to changing environments, and maintaining to prevent breakdowns.

关键词： Adaptation models Service robots Robot sensing systems Cleaning Path planning sensor systems sensors Artificial intelligence Standards Predictive maintenance

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Cloud-based AI Robotics for Precision Pruning of Fruit Trees to Improve Sustainable Farming

Cloud-Based AI Robotics for Precision Pruning of Fruit Trees...

引用

international Symposium on Advanced Computing and Communication (ISACC)

作者： R.C. Ilambirai Barkathulla. A G. Mahalakshmi J. Jagan Babu Prabu K C. Srinivasan Department of Electrical and Electronics Engineering SRM Institute of Science and Technology Chennai Tamil Nadu India Department of Computer Science and Engineering School of Computing Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Computer Science and Engineering Chennai Institute of Technology Chennai Tamil Nadu India Department of Electronics and Communication Engineering R.M.D Engineering College Chennai Tamil Nadu India Department of Electronics and Communication Engineering Gojan School of Business and Technology Chennai Tamil Nadu India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

The crucial agricultural practice of precision pruning fruit trees greatly impacts fruit production yield and quality. Traditional pruning techniques take a lot of time and money because they need skilled workers and are labor-intensive. It suggests a novel cloud-based AI robotics system intended to precisely prune fruit trees to address these issues. This system uses cutting-edge robotics fitted with Convolutional Neural Networks (CNNs) to carry out precise and effective tasks related to pruning. Cloud computing integration makes it possible to process and make real-time decisions, improving the system's flexibility in responding to changing tree conditions and pruning needs. The system's primary parts are robotic arms for accurate cuts, various sensors for analyzing tree structures, and CNN models for maximizing pruning techniques. Early field trials show noticeable gains in operational efficiency and pruning accuracy compared to conventional techniques. This study demonstrates how cloud-integrated AI robotics can transform agricultural practices and improve fruit farming's sustainability and productivity.

关键词： Training Cloud computing Accuracy Crops Robot sensing systems Real-time systems sensor systems Convolutional neural networks robots Farming

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Distributed intelligent sensor system: Partial immersion into a virtualized reality environment

Distributed intelligent sensor system: Partial immersion int...

引用

3rd IEEE international workshop on Haptic, Audio and Visual Environments and their Applications

作者： Abielmona, R Groza, V Univ Ottawa Sch Informat Technol & Engn Ottawa ON K1N 6N5 Canada

ISBN: (纸本)0780388178

This paper discusses the partial immersion of real-time, real-world robotic intelligent sensor agents into a virtualized reality environment. The work also discusses the current solutions for the wireless communication amongst the robots and the network access points, the local intelligence built into the individual agents and the human-computer interaction that allows the human operator to partially immerse himself/herself into the robotic environment.

关键词： intelligent agents

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Interactive learning of world model information for a service robot 3rd

引用

3rd international workshop on sensor based intelligent robots

作者： Kristensen, S Hansen, V Horstmann, S Klandt, J Kondak, K Lohnert, F Stopp, A Daimler Benz Res & Technol Intelligent Syst Grp D-10559 Berlin Germany

ISBN: (纸本)3540669337

In this paper, the problem of generating a suitable environment model for a service robot is addressed. For a service robot to be commercially attractive, it is important that it has a high degree of flexibility and that it can be installed without expert assistance. This means that the representations for doing planning and execution of tasks must be taught on-line and on-site by the user. Here a solution is proposed where the user interactively teaches the robot its representations, using the robot's existing navigation and perception modules. based on a context adaptive architecture and purposive sensing modules it is shown how compact, symbolic representations sufficient for planning and robust execution of tasks can be generated.

关键词： Mobile robots

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A robust Monte-Carlo algorithm for multi-robot localization

引用

3rd international workshop on Multi-Robot Systems

作者： Amiranashvili, V Lakemeyer, G Rhein Westfal TH Aachen D-52056 Aachen Germany

ISBN: (纸本)1402033885

This paper presents a new algorithm for the problem of multi-robot localization in a known environment. The approach is based on the mutual refinement by robots of their beliefs about the global poses, whenever they detect each other's paths. The robots try to detect the paths of other robots by comparing their own perception sensor information to that "seen" by other robots. This way the relative poses of the robots can be determined, which in turn enables the exchange of the beliefs about the global poses.

关键词： multiple robots Monte Carlo localization

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Enabling autonomous sensor-sharing for tightly coupled cooperative tasks

引用

3rd international workshop on Multi-Robot Systems

作者： Parker, LE Chandra, M Tang, F Univ Tennessee Dept Comp Sci Distributed Intelligence Lab Knoxville TN 37996 USA

ISBN: (纸本)1402033885

This paper presents a mechanism enabling robot team members to share sensor information to achieve tightly-coupled cooperative tasks. This approach, called ASyMTRe, is based on a distributed extension of schema theory that allows schema-based building blocks to be interconnected in many ways, regardless of whether they are on the same or different robots. The inputs and outputs of schema are labeled with an information type, inspired by the theory of information invariants. By enabling robots to autonomously configure their distributed schema connections based on the flow of information through the system, robot teams with different collective capabilities are able to generate significantly different cooperative control strategies for solving the same task. We demonstrate the ability of this approach to generate different cooperative control strategies in a proof-of-principle implementation on physical robots performing a simple transportation task.

关键词： sensor-sharing heterogeneous teams multi-robot coalitions

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Direct perception for intelligent robot to grasp an unknown object 3

Direct perception for intelligent robot to grasp an unknown ...

引用

3rd international workshop on Advanced Computational Intelligence and intelligent Informatics, IWACIII 2013

作者： Masuta, Hiroyuki Lim, Hun-Ok Kanagawa University 3-27-1 Rokkakubashi kanagawa-ku Yokohama Kanagawa Japan

This paper describes a robot perception of an unknown object based on perceiving-acting cycle concept for service robots using 3D range sensor. The previous method has problems which are high computational costs and low-accuracy of small object detection to detect an unknown object. We have proposed retinal structure based plane detection method to solve aforementioned problems. The proposed method is constructed by retinal structure based simple plane detection and integrated object plane detection. Furthermore, we have proposed the sensation of grasping based on ecological psychology to perceive the possibility of grasping an object, even if a robot doesn't know the accurate properties of an object. The sensation of grasping affords the possibility of action to a robot directly without inference from physical information such as size, posture, and diameter. As experimental results, we show that the computational cost of the proposed method is less than compared to traditional plane detection method. And, we show that the robot can detect a fallen cup that is unknown object, and then grasp a fallen cup.

关键词： intelligent robots

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Distributed algorithms for carrying a ladder by omnidirectional robots in near optimal time 3rd

引用

3rd international workshop on sensor based intelligent robots

作者： Asahiro, Y Asama, H Fujita, S Suzuki, I Yamashita, M Kyushu Univ Fukuoka 8128581 Japan RIKEN Inst Phys & Chem Res Wako Saitama 35101 Japan Hiroshima Univ Higashihiroshima 7398511 Japan Univ Wisconsin Milwaukee WI 53201 USA

ISBN: (纸本)3540669337

Consider two omnidirectional robots carrying a ladder, one at each end, in the plane without obstacles. Given start and goal positions of the ladder, what is a time-optimal motion of the robots subject to given constraints on their kinematics such as maximum acceleration and velocity? Using optimal control theory, Chen, Suzuki and Yamashita solved this problem under a kinematic constraint that the speed of each robot must be either 0 or a given constant v at any moment during the motion. Their solution, which requires complicated calculation, is centralized and off-line. The objective of this paper is to demonstrate that even without the complicated calculation, a motion that is sufficiently close to time-optimal can be obtained using a simple distributed algorithm in which each robot decides its motion individually based on the current and goal positions of the ladder.

关键词： robots

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Markov localization for reliable robot navigation and people detection 3rd

引用

3rd international workshop on sensor based intelligent robots

作者： Fox, D Burgard, W Thrun, S Univ Bonn Dept COmp Sci 3 D-5300 Bonn Germany Carnegie Mellon Univ Sch Comp Sci Pittsburgh PA 15213 USA

ISBN: (纸本)3540669337

Localization is one of the fundamental problems in mobile robotics. Without knowledge about their position mobile robots cannot efficiently carry out their tasks. In this paper we present Markov localization as a technique for estimating the position of a mobile robot. The key idea of this technique is to maintain a probability density over the whole state space of the robot within its environment. This way our technique is able to globally localize the robot from scratch and even to recover from localization failures, a property which is essential for truly autonomous robots. The probabilistic framework makes this approach robust against approximate models of the environment as well as noisy sensors. based on a fine-grained, metric discretization of the state space, Markov localization is able to incorporate raw sensor readings and does not require predefined landmarks. It also includes a filtering technique which allows to reliably estimate the position of a mobile robot even in densely populated environments. We furthermore describe, how the explicit representation of the density can be exploited in a reactive collision avoidance system to increase the robustness and reliability of the robot even in situations in which it is uncertain about its position. The method described here has been implemented and tested in several real-world applications of mobile robots including the deployments of two mobile robots as interactive museum tour-guides.

关键词： Mobile robots

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