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3rd International Conference on Signal Processing and Integrated Networks (SPIN)

作者： Majumder, Shibarchi Prasad, Mani Shankar Indian Inst Space Sci & Technol Thiruvananthapuram Kerala India

ISBN: (纸本)9781467391979

path planning algorithms play a significant role in autonomous navigation problems. There are several algorithms to compute the optimal path through a cooperative environment. However, for uncooperative environment, finding the global minima is not certain. There are effective algorithms like dynamic A* (D*), for finding an efficient path in uncooperative two dimensional spaces using the concept of local minima. For three dimensional spaces the problem becomes more complex as the traverse cost is dynamic for Z axis. We propose an algorithm for incremental path finding throughout the flight regime, as a concept modification of D*, to work on 3D environment.

关键词： Incremental path planning Uncooperative Environment path planning algorithm Obstacle Handling Edge Point UAV path-planning

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A speed up approach for search and rescue

A speed up approach for search and rescue

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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Shih, Guan-Rong Tsai, Pei-Hsuan Lin, Chun-Lung Natl Cheng Kung Univ Inst Mfg Informat & Syst Tainan Taiwan Ind Technol Res Inst Dept Informat & Commun Res Labs Chung Hsing Rd Hsinchu Taiwan

ISBN: (纸本)9781538666500

Search and rescue (SAR) is to find and help people who are injured or in danger in difficult environments, such as mountain, marine and rainforest. The time of searching victims should be short to minimize the damage and increase the survival rate. However, searching victim is time-consuming, especially for searching missing people in a large scale area. Many techniques including unmanned aerial vehicle, robot, and auto-car, are applied to assist searching nowadays. This paper proposes a map model with a greedy searching algorithm to guide searchers efficiently finding victims faster and takes UAV as a searching scenario.

关键词： search and rescue UAV path planning algorithm map modeling

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AN INTERNET-OF-THINGS BASED FRAMEWORK FOR COLLABORATIVE MANUFACTURING

AN INTERNET-OF-THINGS BASED FRAMEWORK FOR COLLABORATIVE MANU...

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ASME International Mechanical Engineering Congress and Exposition

作者： Krishnamurthy, Rajesh Cecil, J. Perera, Damith Oklahoma State Univ Oklahoma Alliance Mfg Excellence Stillwater OK 74078 USA Oklahoma State Univ Dept Comp Sci Ctr Cyber Phys Syst Stillwater OK 74078 USA Oklahoma State Univ Dept Comp Sci Stillwater OK 74078 USA

ISBN: (纸本)9780791858356

The exchange of data and information among collaborating partners and resources in a distributed manufacturing system assumes significance especially in today's global economy. In recent years, Internet of Things (IoT) and Cyber Physical Systems (CPS) related practices and technologies have emerged as enablers of collaborative manufacturing and engineering practices. Smart technologies involving Virtual Reality and haptic based interactions are continuing to play an important role n concurrent engineering based methods in distributed contexts. he research presented in this paper explores the design of an IoT based framework for electronics manufacturing involving he use of VR based environments and Cloud computing Technologies. The process domain of interest is electronics manufacturing with an emphasis on Surface Mount assembly of printed circuit boards (PCBs). The VR based assembly environment played a key role in this IoT framework as it supported Concurrent Engineering practices by enabling takeholders in this manufacturing system context to obtain a better understanding of the manufacturing process design while providing 'what if' analysis capabilities for changing customer equirements. Another benefit of such VR based IoT frameworks the potential of such 3D environments to provide effective raining of assembly processes as well as facilitating better derstanding of process design issues from distributed cations.

关键词： Virtual Prototyping Surface Mount Technology path planning algorithm Internet of Things Cyber Physical Systems

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path planning based QoS Routing in VANET

Path Planning based QoS Routing in VANET

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International Conference on Big Data, IoT and Data Science (BID)

作者： Shaikh, Farheen Iqbal Hingoliwala, Hyder Ali JSCOE Dept Comp Engn Pune Maharashtra India

ISBN: (纸本)9781509065936

Vehicular ad hoc networks (VANETs) is an emerging technology which has received lot of attention due to its potential to improve vehicle and road safety, traffic control, efficiency as well as convenience for users. VANET is a sub category of mobile ad hoc network (MANET). A lot of research in VANET is done on routing, broadcasting, Quality of Service (QoS) and security. This paper proposes a novel path planning algorithm for reliable and efficient routing. The proposed system will traditionally distribute the work load over alternate paths in order to avoid congestion and reduce travel cost. It ensures reliable routing with less bandwidth requirement as it manages large size packets by dividing into parts and sending via alternate path. VANET may be affected by attacks on routing leading to altering messages and routes which will affect QoS parameters. The proposed algorithm will also deal with providing security measures over the routing process. Therefore, we obtain routing algorithm subject to multiple QoS constraints for secure communication in VANET.

关键词： Multi-constrained path planning algorithm Vehicular ad hoc network Reliable routing Multi-constrained path planning algorithm Reliable routing Vehicular ad hoc network

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3-D Trajectory planning of Aerial Vehicles Using RRT

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IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY 2017年第3期25卷 1116-1123页

作者： Pharpatara, P. Herisse, B. Bestaoui, Y. Off Natl Etud & Rech Aerosp F-91761 Palaiseau France Geoinformat & Space Technol Dev Agcy Publ Org Bangkok 10210 Thailand Univ Evry Val dEssonne Lab Informat Biol Integrat & Syst Complexes F-91020 Evry France

This brief presents a trajectory planning algorithm for aerial vehicles traveling in 3-D space while avoiding obstacles. The nature of the obstacles can be, for example, radar detection areas, cooperating and non-cooperating vehicles, and so on. Thus, it is a complex trajectory planning problem. The proposed planner is based on the optimal rapidly exploring random tree (RRT*) algorithm. Artificial potential fields are combined with the RRT* algorithm to accelerate the convergence speed to a suboptimal solution by biasing the random state generation. The performance of this framework is demonstrated on a complex missile application in a heterogeneous environment. Indeed, since the air density decreases exponentially with altitude, the maneuverability of the aerial vehicle depending on aerodynamic forces also decreases exponentially with altitude. To face this problem, the shortest paths of Dubins-like vehicles traveling in a heterogeneous environment are used to build the metric. In the simulation results, this framework can find the first solution with fewer iterations than the RRT and the RRT* algorithm. Moreover, the final solution obtained within a given number of iterations is closer to an optimal solution regarding the considered criterion.

关键词： Aerial robotics complex environment optimal control optimal rapidly exploring random tree (RRT*) algorithm path planning algorithm

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Comparison and Analysis of Obstacle Avoiding path planning of Mobile Robot by Using Ant Colony Optimization and Teaching Learning Based Optimization Techniques 1st

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1st International Conference on Information and Communication Technology for Intelligent Systems (ICTIS)

作者： Ansari, A. Q. Ibraheem Katiyar, Sapna Jamia Millia Islamia New Delhi India

ISBN: (纸本)9783319309279;9783319309262

Now a day, one of the prime concerns of mobile robot is path planning, in the area of industrial robotics. A path planning optimization method was proposed to calculate shortest collision free path from source to destination by avoiding static as well as dynamic obstacles. Therefore, it is necessary to select appropriate optimization technique for optimization of paths. Such problems can be solved by metaheuristic methods. This research paper demonstrates the comparison and analysis of two Soft Computing Techniques i.e. Ant Colony Optimization (ACO) and Teaching Learning Based Optimization (TLBO) by simulating respective algorithms for finding shortest path of a Mobile Robot by Obstacle avoidance & path re-planning and path Tracking. Both of these techniques seem to be a promising technique with relatively competitive performances. The ACO has been more widely used in that and it gives good solution with smaller numbers of predetermined parameters in comparison with other algorithms.

关键词： path planning algorithm Teaching learning based optimization (TLBO) Ant colony optimization (ACO) Metaheuristic Pheromone and obstacle avoidance

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Research on a Behavior Control Technique of Crowd Simulation 11

Research on a Behavior Control Technique of Crowd Simulation

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11th International Conference on Computer Science & Education (ICCSE)

作者： Zheng, Yuhui Gu, Pingping Wu, Meiling Wu, Qingfeng Xiamen Univ Software Sch Xiamen Fujian Peoples R China Xiamen Univ Tan Kah Kee Coll Dept Comp Sci Zhangzhou Fujian Peoples R China

ISBN: (纸本)9781509022182

With its imitating the perception and behaviors, scheming for instance, of human beings in virtual space, the crowd simulation technique aims at a truthful reflecting of crowd characteristics. However, for the crowd simulation, the behavior control is the crux. It introduces functions like perception, cognition, decision-making and so forth into motion control, and builds an autonomy model for virtual human, thus achieving the control of virtual crowd. To begin with, this paper introduces theories of behavior and behavior control. Based on it, the thesis presents a behavior control model, which involves perception model, path planning and behavior model. It goes on with the comparison of several behavior control models, and concludes the related control algorithm. Besides, based on the analysis of relevant researches, this paper ends with the indication about the aspects that more attention should be laid to in the field of crowd simulation in the near future.

关键词： crowd simulation behavior control path planning algorithm

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A New path planning and Obstacle Avoidance algorithm in Dynamic Environment 22

A New Path Planning and Obstacle Avoidance Algorithm in Dyna...

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22nd Iranian Conference on Electrical Engineering (ICEE)

作者： Mohammadi, Afshin Rahimi, Meysam Suratgar, Amir Abolfazl Amirkabir Univ Technol Dept Elect Engn Tehran Iran

ISBN: (纸本)9781479944095

By developments of robotics and increments in utilizing this knowledge in different scientific and industrial branches, the issue of path planning, either in intelligent and online state, or by pre-determined algorithms has been arised as one of the discussion fields in control and specially robotics. In the path planning literature, several algorithms have been used repetitively, among which can be mentioned potential field algorithms and intelligent algorithms such as genetic and A-Star, in which the main challenge is to find an obstacle free path, not considering capabilities like computation time, considering obstacles in path finding procedure. In this paper, we developed a new path planning algorithm, not only find an obstacle-free path but also has an optimal computation time in term of obstacle importance and consider the issues like adjustable obstacle avoidance and smoothness of the final path. The intention of this paper is introducing a path planning which is able to be applied in a typical needle penetration surgery. The proposed algorithm, by suitable environment segmentation, as hexagonal segmentation, concludes to a path, that is very smoother than pathes which are resulted in other traditional algorithms.

关键词： collision avoidance medical robotics mobile robots surgery dynamic environment needle penetration surgery obstacle avoidance algorithm path planning algorithm Collision avoidance Heuristic algorithms Indexes Needles path planning Robots Surgery

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Classifying and Passing 3D Obstacles for Autonomous Driving 18

Classifying and Passing 3D Obstacles for Autonomous Driving

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18th IEEE International Conference on Intelligent Transportation Systems

作者： Delp, Michael Nagasaka, Naoki Kamata, Nobuhide James, Michael R. Toyota Res Inst North Amer 1555 Woodridge Ave Ann Arbor MI 48105 USA

ISBN: (纸本)9781467365963

Highly automated driving in real world situations requires perception and planning to account for other forms of human locomotion, principally bicycles, and pedestrians, in addition to vehicles. Here we present a complete perception-planning-control system with high quality perception including object classification and tracking, and a path planning algorithm that makes use of probabilistic classification results. Our classification algorithm is fast enough to provide results for the vast majority of objects in on-line operation, but to ensure output for real-time decision-making the computation and integration of classification results is done using an anytime algorithm. Our focus is on safe driving behavior in the presence of dynamic obstacles on the side of the road, which are typically bicycles, using LIDAR data. Our resulting system is extensively tested in real-world situations, and shows good performance on a large test set of interactions with bicycles.

关键词： bicycles image classification intelligent transportation systems object tracking path planning pedestrians road safety road vehicles 3D obstacles LIDAR data anytime algorithm automated driving autonomous driving classification algorithm dynamic obstacles high quality perception human locomotion object classification path planning algorithm perception-planning-control system probabilistic classification real-time decision-making safe driving behavior vehicles Bicycles Laser radar Radar tracking Robot sensing systems Three-dimensional displays

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Magnetic field SLAM exploration: frequency domain Gaussian processes and informative route planning

Magnetic field SLAM exploration: frequency domain Gaussian p...

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European Conference on Mobile Robots

作者： Kemppainen, Anssi Vallivaara, Ilari Roning, Juha Univ Oulu Dept Comp Sci & Engn SF-90100 Oulu Finland

ISBN: (纸本)9781467391634

In this paper, we consider magnetic field SLAM exploration using a mobile robot with a magnetometer and wheel encoders. We propose computationally feasible solutions to model magnetic fields using frequency domain Gaussian processes. In addition, we propose a path planning algorithm to efficiently collect a given level of accuracy for magnetic field models. The path planning is based on partition of shortest paths into blocks with similar information content and implementing depth-first search among these blocks. Finally, we propose an exploration-exploitation algorithm enabling real-world mobile robot SLAM exploration solutions with motion uncertainties. SLAM is presented with Rao-Blackwellized particle filters where robot's path hypothesis are presented with particles together with a separate magnetic field model for each particle. We conducted SLAM exploration experiments using real magnetic field data in a simulated environment. Simulation parameters were tuned to approximate ICreate robot's motion uncertainties and MicroMag3 magnetometer's sensor noise, together with the robot's inclination uncertainties. Simulations demonstrated for the first time that we were able to build actual magnetic field SLAM exploration. The results indicate that, with frequency domain Gaussian processes, we are able to obtain desirable convergence of path distribution, although, with the selected particle filter SLAM approach, the localization accuracy was not desirable.

关键词： Gaussian processes SLAM (robots) frequency-domain analysis magnetic sensors magnetometers mobile robots particle filtering (numerical methods) path planning robot vision tree searching ICreate robot motion uncertainties MicroMag3 magnetometer sensor noise Rao-Blackwellized particle filters depth-first search exploration-exploitation algorithm frequency domain Gaussian processes informative route planning magnetic field SLAM exploration mobile robot SLAM exploration path planning algorithm robot inclination uncertainties wheel encoders Frequency-domain analysis Magnetic domains Magnetic separation Magnetometers Simultaneous localization and mapping Yttrium Frequency-domain analysis magnetometers Gaussian processes path planning Depth--first search simultaneous localization and mapping Mobile robots Tree searching supersonic low altitude missile robot vision Magnetic domain Magnetic sensors Magnetic separation Rare earths yttrium

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