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Relevant bibliographies by topics / Collision optimization

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Academic literature on the topic 'Collision optimization'

Author: Grafiati

Published: 4 June 2021

Last updated: 4 February 2022

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Journal articles on the topic "Collision optimization"

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Xu, Qingyang, Chuang Zhang, and Ning Wang. "Multiobjective Optimization Based Vessel Collision Avoidance Strategy Optimization." Mathematical Problems in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/914689.

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The vessel collision accidents cause a great loss of lives and property. In order to reduce the human fault and greatly improve the safety of marine traffic, collision avoidance strategy optimization is proposed to achieve this. In the paper, a multiobjective optimization algorithm NSGA-II is adopted to search for the optimal collision avoidance strategy considering the safety as well as economy elements of collision avoidance. Ship domain and Arena are used to evaluate the collision risk in the simulation. Based on the optimization, an optimal rudder angle is recommended to navigator for collision avoidance. In the simulation example, a crossing encounter situation is simulated, and the NSGA-II searches for the optimal collision avoidance operation under the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS). The simulation studies exhibit the validity of the method.

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Li, Jinxin, Hongbo Wang, Wei Zhao, and Yuanyuan Xue. "Ship’s Trajectory Planning Based on Improved Multiobjective Algorithm for Collision Avoidance." Journal of Advanced Transportation 2019 (April 9, 2019): 1–12. http://dx.doi.org/10.1155/2019/4068783.

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With vigorous development of the maritime trade, many intelligent algorithms have been proposed to avoid collisions due to resulting casualties and increased costs. According to the international regulations for preventing collisions at sea (COLREGs) and the self-evolution ability of the intelligent algorithm, the collision avoidance trajectory can be more consistent with the requirements of reality and maritime personnel. In this paper, the optimization of ship collision avoidance strategies is realized by both an improved multiobjective optimization algorithm NSGA-II and the ship domain under the condition of a wide sea area without any external disturbances. By balancing the safety and economy of ship collision avoidance, the avoidance angle and the time to the action point are used as the variables encoded by the algorithm, and the fuzzy ship domain is used to calculate the collision avoidance risk to achieve collision avoidance. The simulation results show that the proposed method can optimize the ship collision avoidance strategy and provide a reasonable scheme for ship navigation.

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Mohamed, Abdulrahman. "Novel approach for anti-collision planning optimization in directional wells." International Journal of Engineering & Technology 9, no. 2 (April 3, 2020): 333. http://dx.doi.org/10.14419/ijet.v9i2.30306.

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One of the most application of the directional drilling is drilling multiple wells from one location or platform. In drilling multiple wells from one location the major problem that faced is avoiding the collision with the offset wells that drilled near the proposed well in the same region. Therefore, the Potential of Collison between the wells can cause severe catastrophic accidents such as an explosion or oil spill. Several measurements of proximity calculation or methods have been adopted to control the distance between the wells, avoid the Collison, increas-ing the clearance along with smoothing the trajectory, Reducing the drilling time based on the anti-collision rules. A real case study of an offshore directional horizontal well drilled from the platform is studied through the paper. The proposed well is drilled in the neighboring of three Offset wells that should be Planned completely to avoid the Collison with them. The well is planned through an advanced anti-collision method that results in preventing the collision of well with optimized drilling performance through Oriented separation factor (OSF). This factor yields appropriate separation with OSF greater than 5. This yield efficient separation with offset well 1, offset well 2 and offset well 3 greater thant5, In addition to optimized drilling performance of 84% drilling versus 16% sliding that results in the completion of the well in 50 days with positive income that result in 8.55 Return on Investment (ROI).

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Ma, Wen Yao, and Jia Xuan Yang. "Collision Avoidance Strategy Optimization of Ship’s Speed Alteration with Bacterial Foraging Algorithm." Applied Mechanics and Materials 278-280 (January 2013): 1318–22. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.1318.

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When ship navigates at sea, collision avoidance of ship’s speed alteration is frequently adopted by officer on watch in order to prevent from forming collision situation with target ship(s). Bacterial foraging algorithm (BFA) that imitates the social foraging behavior of Escherichia coli is an optimal search method suitable for complex problems. This research adopts the bacterial foraging algorithm to find the speed alteration collision avoidance strategy from an economical viewpoint, combining the international regulations for preventing collisions at sea (COLREGS) and the safety domain of ship. An optimal time of changing speed, amplitude of speed alteration and navigation restoration time will also be provided. The effectiveness of the algorithm has been verified by simulation. The study offers new thinking and a practical method for collision avoidance decision.

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Lazarowska, Agnieszka. "Safe Ship Control Method with the Use of Ant Colony Optimization." Solid State Phenomena 210 (October 2013): 234–44. http://dx.doi.org/10.4028/www.scientific.net/ssp.210.234.

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Nowadays Integrated Bridge Systems are applied on board a ship to increase safety of navigation. These systems consist of many electronic devices such as radar, ECDIS and autopilot, which aid the deck officer in the process of conducting navigation. Despite that, ship accidents caused by human error still occur. The paper presents new method of safe ship control in collision situations. Ant Colony Optimization is applied to determine safe ship trajectory. Developed algorithm is applicable for situations in restricted waters, where most of collision situations occur. International Regulations for Preventing Collisions at Sea (COLREGs) are taken into consideration in the process of solution construction. The task of collision avoidance at sea is defined as dynamic optimization problem with the use of static and dynamic constraints. Static constraints are represented by lands, canals, shallows, fairways, while other ships constitute dynamic constraints. Described method was implemented in MATLAB programming language. Performed simulation tests results of encounter situations with one target ship as well as with many target vessels are presented. Received solutions confirm successful application of this method to the problem of ships collisions avoidance. Developed algorithm deals also with more complex situations. This new algorithm is planned to be implemented in anti-collision decision support system on board a ship, what would contribute to enhance safety of maritime transport.

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Xia, Guoqing, Zhiwei Han, Bo Zhao, and Xinwei Wang. "Local Path Planning for Unmanned Surface Vehicle Collision Avoidance Based on Modified Quantum Particle Swarm Optimization." Complexity 2020 (April 13, 2020): 1–15. http://dx.doi.org/10.1155/2020/3095426.

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An unmanned surface vehicle (USV) plans its global path before the mission starts. When dynamic obstacles appear during sailing, the planned global path must be adjusted locally to avoid collision. This study proposes a local path planning algorithm based on the velocity obstacle (VO) method and modified quantum particle swarm optimization (MQPSO) for USV collision avoidance. The collision avoidance model based on VO not only considers the velocity and course of the USV but also handles the variable velocity and course of an obstacle. According to the collision avoidance model, the USV needs to adjust its velocity and course simultaneously to avoid collision. Due to the kinematic constraints of the USV, the velocity window and course window of the USV are determined by the dynamic window approach (DWA). In summary, local path planning is transformed into a multiobjective optimization problem with multiple constraints in a continuous search space. The optimization problem is to obtain the USV’s optimal velocity variation and course variation to avoid collision and minimize its energy consumption under the rules of the International Regulations for Preventing Collisions at Sea (COLREGs) and the kinematic constraints of the USV. Since USV local path planning is completed in a short time, it is essential that the optimization algorithm can quickly obtain the optimal value. MQPSO is primarily proposed to meet that requirement. In MQPSO, the efficiency of quantum encoding in quantum computing and the optimization ability of representing the motion states of the particles with wave functions to cover the whole feasible solution space are combined. Simulation results show that the proposed algorithm can obtain the optimal values of the benchmark functions and effectively plan a collision-free path for a USV.

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Machmudah, Affiani, and Setyamartana Parman. "Bezier Curve Collision-Free Route Planning Using Meta-Heuristic Optimization." International Journal of Artificial Intelligence & Robotics (IJAIR) 3, no. 1 (May 31, 2021): 1–14. http://dx.doi.org/10.25139/ijair.v3i1.3821.

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A collision-free route is very important for achieving sustainability in a manufacturing process and vehicle robot trajectories that commonly operate in a hazardous environment surrounded by obstacles. This paper presents a collision avoidance algorithm using a Bezier curve as a route path. The route planning is modeled as an optimization problem with the objective optimization is to minimize the route length considering an avoiding collision constraint. The collision-avoidance algorithm based on curve point analysis is developed incorporating metaheuristic optimizations, namely a Genetic Algorithm (GA) and a Grey Wolf Optimizer (GWO). In the collision avoidance algorithm, checking of curve point's position is important to evaluate the individual fitness value. The curve points are analyzed in such a way so that only the paths which are outside the obstacle area are selected. In this case, besides the minimum length as a fitness function, the constraint is the position of curve points from an obstacle. With the help of meta-heuristic optimization, the developed collision avoidance algorithm has been applied successfully to different types of obstacle geometries. The optimization problem is converted to the maximization problem so that the highest fitness value is used to measure the performance of the GA and GWO. In general, results show that the GWO outperforms the GA, where it exhibits the highest fitness value. However, the GA has shown better performance for the narrow passage problem than that of the GWO. Thus, for future research, implementing the hybrid technique combining the GA and the GWO to solve the advanced path planning is essential.

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Custură-Crăciun, Dan, Daniel Cochior, and Corneliu Neagu. "Optimization of Collision Detection in Surgical Simulations." ACTA Universitatis Cibiniensis 64, no. 1 (November 1, 2014): 34–39. http://dx.doi.org/10.2478/aucts-2014-0007.

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Abstract Just like flight and spaceship simulators already represent a standard, we expect that soon enough, surgical simulators should become a standard in medical applications. A simulations quality is strongly related to the image quality as well as the degree of realism of the simulation. Increased quality requires increased resolution, increased representation speed but more important, a larger amount of mathematical equations. To make it possible, not only that we need more efficient computers, but especially more calculation process optimizations. A simulator executes one of the most complex sets of calculations each time it detects a contact between the virtual objects, therefore optimization of collision detection is fatal for the work-speed of a simulator and hence in its quality

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Liu, Jiang, Bai Gen Cai, Yun Peng Wang, and Jian Wang. "Simulation Analysis of a PSO-Based Vehicle Collision Avoidance Method under Cooperative Vehicle Infrastructure Environment." Applied Mechanics and Materials 241-244 (December 2012): 1539–44. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.1539.

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Vehicle safety is of great importance to improve the capability and performance of the transportation system. To deal with safety threats most probably caused by the vehicle collisions in unsignalized intersections, concept of vehicle infrastructure cooperation provides a perspective and challenging solution to enable sufficient information interaction by V2V and V2I communication, which make it feasible to avoid collisions more autonomously. In vehicle collision avoidance scheme, decision making of vehicle braking control is crucial for emergent situations when safety alerts are not reacted by the driver. In this paper, a novel cooperative vehicle collision avoidance method based on particle swarm optimization is proposed, with an integrated fitness updating criteria considering both safety interval and relative continuity of vehicle deceleration. With a simulation analysis approach, the proposed collision avoiding solution is validated in a real road oriented scenario, and the results demonstrate its effectiveness and advantages to reduce collision and achieve safety assurance under cooperative vehicle infrastructure environment.

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Zheng, Yisong, Xiuguo Zhang, Zijing Shang, Siyu Guo, and Yiquan Du. "A Decision-Making Method for Ship Collision Avoidance Based on Improved Cultural Particle Swarm." Journal of Advanced Transportation 2021 (January 15, 2021): 1–31. http://dx.doi.org/10.1155/2021/8898507.

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In the process of ship collision avoidance decision making, steering collision avoidance is the most frequently adopted collision avoidance method. In order to obtain an effective and reasonable steering angle, this paper proposes a decision-making method for ship collision avoidance based on improved cultural particle swarm. Firstly, the ship steering angle direction is to be determined. In this stage, the Kalman filter is used to predict the ship’s trajectory. According to the prediction parameters, the collision risk index of the ship is calculated and the situation with the most dangerous ship is judged. Then, the steering angle direction of the ship is determined by considering the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs). Secondly, the ship steering angle is to be calculated. In this stage, the cultural particle swarm optimization algorithm is improved by introducing the index of population premature convergence degree to adaptively adjust the inertia weight of the cultural particle swarm so as to avoid the algorithm falling into premature convergence state. The improved cultural particle swarm optimization algorithm is used to find the optimal steering angle within the range of the steering angle direction. Compared with other evolutionary algorithms, the improved cultural particle swarm optimization algorithm has better global convergence. The convergence speed and stability are also significantly improved. Thirdly, the ship steering angle direction decision method in the first stage and the ship steering angle decision method in the second stage are integrated into the electronic chart platform to verify the effectiveness of the decision-making method of ship collision avoidance presented in this paper. Results show that the proposed approach can automatically realize collision avoidance from all other ships and it has an important practical application value.

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Dissertations / Theses on the topic "Collision optimization"

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Lithgow, Anthony R. "Collision-free trajectory optimization for multiple robotic manipulators." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0004/MQ32490.pdf.

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Morris, Bradford Shepherd J. E. Shepherd J. E. "Charge-exchange collision dynamics and ion engine grid geometry optimization /." Diss., Pasadena, Calif. : California Institute of Technology, 2007. http://resolver.caltech.edu/CaltechETD:etd-02282007-154751.

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Lepird, John R. "Multi-objective optimization of next-generation aircraft collision avoidance software." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98566.

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Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2015.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
"June 2015." Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 85-90).
Developed in the 1970's and 1980's, the Traffic Alert and Collision Avoidance System (TCAS) is the last safety net to prevent an aircraft mid-air collision. Although TCAS has been historically very effective, TCAS logic must adapt to meet the new challenges of our increasingly busy modern airspace. Numerous studies have shown that formulating collision avoidance as a partially-observable Markov decision process (POMDP) can dramatically increase system performance. However, the POMDP formulation relies on a number of design parameters modifying these parameters can dramatically alter system behavior. Prior work tunes these design parameters with respect to a single performance metric. This thesis extends existing work to handle more than one performance metric. We introduce an algorithm for preference elicitation that allows the designer to meaningfully define a utility function. We also discuss and implement a genetic algorithm that can perform multi-objective optimization directly. By appropriately applying these two methods, we show that we are able to tune the POMDP design parameters more effectively than existing work.
by John R. Lepird.
S.M.

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Degenhardt, Richard Kennedy III. "Self-collision avoidance through keyframe interpolation and optimization-based posture prediction." Thesis, University of Iowa, 2014. https://ir.uiowa.edu/etd/1446.

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Simulating realistic human behavior on a virtual avatar presents a difficult task. Because the simulated environment does not adhere to the same scientific principles that we do in the existent world, the avatar becomes capable of achieving infeasible postures. In an attempt to obtain realistic human simulation, real world constraints are imposed onto the non-sentient being. One such constraint, and the topic of this thesis, is self-collision avoidance. For the purposes of this topic, a posture will be defined solely as a collection of angles formed by each joint on the avatar. The goal of self-collision avoidance is to eliminate the formation of any posture where multiple body parts are attempting to occupy the exact same space. My work necessitates an extension of this definition to also include collision avoidance with objects attached to the body, such as a backpack or armor. In order to prevent these collisions from occurring, I have implemented an effort-based approach for correcting afflicted postures. This technique specifically pertains to postures that are sequenced together with the objective of animating the avatar. As such, the animation's coherence and defining characteristics must be preserved. My approach to this problem is unique in that it strategically blends the concept of keyframe interpolation with an optimization-based strategy for posture prediction. Although there has been considerable work done with methods for keyframe interpolation, there has been minimal progress towards integrating a realistic collision response strategy. Additionally, I will test this optimization-based approach through the use of a complex kinematic human model and investigate the use of the results as input to an existing dynamic motion prediction system.

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Woerner, Kyle. "COLREGS-Compliant Autonomous Collision Avoidance Using Multi-Objective Optimization with Interval Programming." Thesis, Monterey, California. Naval Postgraduate School, 2014. http://hdl.handle.net/10945/43076.

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CIVINS
High contact density environments are becoming ubiquitous in autonomous marine vehicle (AMV) operations. Safely managing these environments and their mission greatly taxes platforms. AMV collisions will likely increase as contact density in- creases. In situations where AMVs are not performing a collaborative mission but are using shared physical space such as multiple vehicles in the same harbor, a high demand exists for safe and e cient operation to minimize mission track deviations while preserving the safety and integrity of mission platforms. With no existing pro- tocol for collision avoidance of AMVs, much e ort to date has focused on individual ad hoc collision avoidance approaches that are self-serving, lack the uniformity of eet-distributed protocols, and disregard the overall eet e ciency when scaled to being in a contact-dense environment. This research shows that by applying interval programming and a collision avoidance protocol such as the International Regulations for Prevention of Collisions at Sea (COLREGS) to a eet of AMVs operating in the same geographic area, the eet achieves nearly identical e ciency concurrent with signi cant reductions in the collisions observed. A basic collision avoidance protocol was analyzed against a COLREGS-based algorithm while parameters key to collision avoidance were studied using Monte Carlo methods and regression analysis of both real-world and simulated statistical data. A testing metric was proposed for declaring AMVs as \COLREGS-compliant" for at-sea operations. This work tested ve AMVs simultaneously with COLREGS collision avoidance{the largest test known to date.

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Smith, Kyle A. (Kyle Alexander). "Collision avoidance system optimization for closely spaced parallel operations through surrogate modeling." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/82491.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2013.
This electronic version was submitted and approved by the author's academic department as part of an electronic thesis pilot project. The certified thesis is available in the Institute Archives and Special Collections.
"June 2013." Cataloged from department-submitted PDF version of thesis
Includes bibliographical references (p. 103-106).
The Traffic Alert and Collision Avoidance System (TCAS) is mandated worldwide to protect against aircraft mid-air collisions. One drawback of the current TCAS design is limited support for certain closely spaced parallel runway operations. TCAS alerts too frequently, leading pilots to often inhibit Resolution Advisories during approach. Research is underway on the Airborne Collision Avoidance System X (ACAS X), a next-generation collision avoidance system that will support new surveillance systems and air traffic control procedures. ACAS X has been shown to outperform TCAS for enroute encounter scenarios. However, the design parameters that are tuned for the enroute environment are not appropriate for closely spaced parallel operations (CSPO). One concept to enhance the safety of CSPO is a procedure-specific mode of the logic that minimizes nuisance alerts while still providing collision protection. This thesis describes the application of surrogate modeling and automated search for the purpose of tuning ACAS X for parallel operations. The performance of the tuned system is assessed using a data-driven blunder model and an operational performance model. Although collision avoidance system development normally relies on human judgment and expertise to achieve ideal behavior, surrogate modeling is efficient and effective in tuning ACAS X for CSPO as the tuned logic outperforms TCAS in terms of both safety and operational suitability
by Kyle A. Smith.
S.M.

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Gonzalez-Carrascosa, Partida Ricardo. "Optimizing manoeuvres for long collision avoidance active system of a car." Thesis, Högskolan i Skövde, Institutionen för teknik och samhälle, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-8502.

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This project presents the development of a collision avoidance active system for cars.There is a large interest in developing avoidance system in the automotive industry since the accidents are of such nature that can be avoided if the system works as desirable e.g., in animal crossing or having the car in front stopping without the driver noticing. A control system is designed to avoid collisions by acting on the steer and brakes of a car. An algorithm is developed to optimize a fuzzy logic controller which actuates on the steer and brakes of the car. The algorithm optimizes the inputs of the car, i.e. steer and brake, to avoid the collision with the object. The optimization of the trajectory implies that the car returns to the original lane and it is the minimum time possible inthe other lane. The object is situated at different distances and the initial speed of the car also varies depending on the situations. The results are obtained by using a car model that is developed in this project in conjunction with the tyre model, [1]. Simulations show that it performs collision avoidance manoeuvres in different conditions. Furthermore, improvements of the present work are suggested that are believed to further enhance the presented algorithm.

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Han, Kyung Min. "Collision free path planning algorithms for robot navigation problem." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/5021.

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Thesis (M.S.)--University of Missouri-Columbia, 2007.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on September 29, 2008) Includes bibliographical references.

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Spencer, John Edward. "ION MOTION AND AN OPTIMIZATION OF TANDEM MASS SPECTROMETRY." UKnowledge, 2005. http://uknowledge.uky.edu/gradschool_theses/211.

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Quadrupole ion trap(QIT) mass spectrometry has become one of the most widelyused tools in the analysis of the structure of small molecules. The motion of the ionsstored in the quadrupole ion trap is extremely important. This ion motion within thequadrupole ion trap is controlled by several factors including the m/z ratio and thecollisional cross section of the ion. Investigation of ion motion within the QIT has thepotential to elucidate a new way to separate ions based on these factors. DC tomographyexperiments allow for the trajectory of the ion motion to be measured withoutmodifications to the ion trap. The ability to use DC tomography for separation ofisomeric ions on a commercial GC/MS system was investigated.Investigation of the mass range within the ion trap is necessary for the analysis ofa wide range of molecules. The ability of the quadrupole ion trap to perform MS/MSanalyses can provide insight into the structural information of many compounds.However, there exists a low mass cut-off (LMC) within the quadrupole ion trap and thusinformation about the low m/z fragments from a parent ion is lost. Schwartz and coworkerspresented a new technique labeled pulsed q dissociation (PQD) at the 53rdAnnual ASMS Conference in San Antonio TX in 2005. PQD eliminates the LMC byperforming CID at a qz of 0.4 but, then immediately lowering the q level before the massscan in a linear ion trap. By operating the quadrupole ion trap in this same manner, lowm/z product ions can be detected. This technique and elucidation of the energetic processcontained within PQD were explored further using a modified commercial quadrupoleion trap and the results discussed in this work.

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Bishnoi, Abhiraj. "GPU-Assisted Collision Avoidance for Trajectory Optimization : Parallelization of Lookup Table Computations for Robotic Motion Planners Based on Optimal Control." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-290587.

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One of the biggest challenges associated with optimization based methods forrobotic motion planning is their extreme sensitivity to a good initial guess,especially in the presence of local minima in the cost function landscape.Additional challenges may also arise due to operational constraints, robotcontrollers sometimes have very little time to plan a trajectory to perform adesired function. To work around these limitations, a common solution is tosplit the motion planner into an offline phase and an online phase. The offlinephase entails computing reference trajectories for varying parameterizationsof the task space in the form of a lookup table. During the online phase,a stripped down version of the optimizer is supplied with a suitable initialguess from the lookup table using the current state estimate of the robot andits surrounding bodies. This method helps in alleviating problems related toboth local minima and operational time constraints, by seeding the optimizerwith a suitable initial guess that allows it to converge to the global minimummuch faster.The problem however, shifts to the computational complexity of computinga lookup table of reference trajectories for a fine enough discreti- zation ofthe input state space. For many robotic scenarios of interest, it is oftenimpractical and sometimes computationally infeasible to compute a look uptable using a serial, single core implementation of the offline phase of a motionplanner. The main contribution of this work is to develop and evaluate amethod for reducing the time spent on computing a lookup table of referencetrajectories during the offline phase of motion planners based on optimalcontrol. We implement a method to offload the computation of collisionavoidance constraints during trajectory optimization on a Graphics ProcessingUnit (GPU), while simultaneously benefiting from a task based approach todistribute lookup table computations for independent subsets of the input statespace across multiple processes on a cluster of machines. We demonstrate theefficacy of the proposed method in a practical setting by implementing andevaluating it within a representative motion planner based on optimal control.We observe that the implemented method is 115x faster than the originalserial version of the planner, using 86 processes on 5 machines with standardserver grade hardware and 5 Graphics Processing Units in total. Additionally,we observe that the implemented method results in solutions identical to theoriginal serial version in 96.6% of cases, lending credibility for its use inrobotic motion planning.
En av de största utmaningarna med optimeringsbaserade metoder för rörelseplaneringinom robotik är deras extrema känslighet för en bra initial gissning,särskilt i närvaro av lokala minima i kostnadsfunktionslandskapet. Ytterligareutmaningar kan också uppstå på grund av operativa begränsningar. Robotkontrollerhar ibland väldigt lite tid att planera en väg för att utföra en önskadfunktion. För att kringgå dessa begränsningar är en vanlig lösning att dela upprörelseplaneraren i en offline-fas och en online-fas. Offlinefasen inkluderarberäkning av referensvägar för olika punkter i ingångstillståndsutrymmet iform av en uppslagstabell. Under online-fasen levereras en avskalad versionav optimeraren med en lämplig initial gissning från uppslagstabellen medden aktuella uppskattningen av roboten och dess omgivande kroppar. Dennametod hjälper till att lindra problem relaterade till både lokala minima ochdriftstidsbegränsningar genom att sådd optimeraren med en lämplig initialgissning som gör att den kan konvergera till det globala minimumet mycketsnabbare.Problemet flyttas emellertid nu till beräkningskomplexiteten för att beräknaen uppslagstabell över referensvägar för ett tillräckligt fint utrymme för ingångstillståndsutrymmet.För många robotscenarier av intresse är det ofta opraktisktoch ibland beräkningsmässigt omöjligt att beräkna en uppslagstabell med hjälpav en seriell, enda kärnimplementering av offline-fasen i en rörelseplanner.Huvudbidraget till detta arbete är att utveckla och utvärdera en metod för attminska tiden som används för att beräkna en uppslagstabell över referensvägarunder offline-fasen för rörelsesplanerare baserat på optimal kontroll. Vi implementeraren metod för att utföra en kollision undvika en grafikbehandlingsenhet(GPU), medan du använder en uppgiftsbaserad metod för att distribuerauppslagningsberäkningar för oberoende delmängder av inmatningsutrymmeöver flera processer i ett kluster av maskiner. Vi demonstrerar effektivitetenav den föreslagna metoden i en praktisk miljö genom att implementeraoch utvärdera den inom en representativ rörelseplanner baserat på optimalkontroll. Vi noterar att den implementerade metoden är 115 gånger snabbareän den ursprungliga serieversionen av schemaläggaren, med 86 processer på 5maskiner med standardhårdvara och totalt 5 GPU: er. Dessutom observerarvi att den implementerade metoden resulterar i lösningar som är identiskamed den ursprungliga serieversionen i mer än 96,6 % av fallen, vilket gertrovärdighet för dess användning i robotrörelse planering.

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Books on the topic "Collision optimization"

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Mog, R. A. Global nonlinear optimization of spacecraft protective structures design. [Marshall Space Flight Center, Ala.]: National Aeronautics and Space Administration, George C. Marshall Space Flight Center, 1990.

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P, Rowe Sean, Breininger David R, and United States. National Aeronautics and Space Administration., eds. Temporal, spatial, and diurnal patterns in avian activity at the Shuttle Landing Facility, John F. Kennedy Space Center, Florida, U.S.A. [Washington, D.C: National Aeronautics and Space Administration, 1997.

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Book chapters on the topic "Collision optimization"

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Yu, Xiaolei, Zhimin Zhao, and Xuezhou Zhang. "Optimization Algorithm and RFID System Physical Anti-Collision." In Physical Anti-Collision in RFID Systems, 157–99. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0835-3_5.

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Morselli, Alessandro, Roberto Armellin, Pierluigi Di Lizia, and Franco Bernelli-Zazzera. "Rigorous Global Optimization for Collision Risk Assessment on Perturbed Orbits." In Springer Optimization and Its Applications, 237–67. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41508-6_9.

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Gavrilova, Marina L., and Jon Rokne. "Collision Detection Optimization in a Multi-particle System." In Lecture Notes in Computer Science, 105–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47789-6_11.

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Sathish, P., and D. Krishna Reddy. "Predictive Data Optimization of Doppler Collision Events for NavIC System." In Numerical Optimization in Engineering and Sciences, 583–89. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3215-3_57.

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Ying, Tan. "Optimization Used in the Collision Problems and Their Application." In 2012 International Conference on Information Technology and Management Science(ICITMS 2012) Proceedings, 725–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34910-2_82.

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Bing, He, Lv Yue, and Jing Mi. "Self-collision Detection Optimization Method in the Arm Clothes Simulation." In Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems, 634–41. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2666-9_64.

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Zhao, Wei, Li-Jun Li, and Cheng-Shou Chen. "Research on Collision Detection Algorithm Based on Particle Swarm Optimization." In Entertainment for Education. Digital Techniques and Systems, 602–9. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14533-9_61.

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Liu, Lisang, Dongwei He, Ying Ma, Tianjian Li, and Jianxing Li. "Research on Ships Collision Avoidance Based on Chaotic Particle Swarm Optimization." In Advances in Smart Vehicular Technology, Transportation, Communication and Applications, 230–39. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70730-3_28.

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Vergé, Christelle, Jérôme Morio, Pierre Del Moral, and Juan Carlos Dolado Pérez. "Probabilistic Safety Analysis of the Collision Between a Space Debris and a Satellite with an Island Particle Algorithm." In Springer Optimization and Its Applications, 443–57. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41508-6_17.

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Tianzhu, Wang, Li Wenhui, Wang Yi, Ge Zihou, and Han Dongfeng. "An Adaptive Stochastic Collision Detection Between Deformable Objects Using Particle Swarm Optimization." In Lecture Notes in Computer Science, 450–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11732242_40.

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Conference papers on the topic "Collision optimization"

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Altman, Eitan, Tania Jiménez, Nelson Vicuna, and Richard Márquez. "Coordination games over Collision Channels." In 6th International ICST Symposium on Modeling and Optimization. IEEE, 2008. http://dx.doi.org/10.4108/icst.wiopt2008.3224.

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Salemme, Giuseppina, Roberto Armellin, and Pierluigi Di Lizia. "Continuous-thrust collision avoidance manoeuvres optimization." In AIAA Scitech 2020 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2020. http://dx.doi.org/10.2514/6.2020-0231.

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Lei, Gang, Chunyan Bao, and Xianjue Liu. "Finite Element Analysis of Head-Ground Collision." In 2008 International Workshop on Modelling, Simulation and Optimization (WMSO). IEEE, 2008. http://dx.doi.org/10.1109/wmso.2008.85.

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Zhang, Xiaojing, Alexander Liniger, Atsushi Sakai, and Francesco Borrelli. "Autonomous Parking Using Optimization-Based Collision Avoidance." In 2018 IEEE Conference on Decision and Control (CDC). IEEE, 2018. http://dx.doi.org/10.1109/cdc.2018.8619433.

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Sislak, David, Premysl Volf, Michal Pechoucek, Niranjan Suri, David Nicholson, and David Woodhouse. "Optimization-Based Collision Avoidance for Cooperating Airplanes." In 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology. IEEE, 2009. http://dx.doi.org/10.1109/wi-iat.2009.180.

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Wang, Paul T. R., and Yoon K. Hong. "Collision awareness multiple access networks performance optimization." In the 29th conference. New York, New York, USA: ACM Press, 1997. http://dx.doi.org/10.1145/268437.268744.

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Wang, Lixing, Yingjing Shi, and Rui Li. "An image-based collision detection optimization algorithm." In 2015 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP). IEEE, 2015. http://dx.doi.org/10.1109/chinasip.2015.7230395.

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Burnett, R. "Application of stochastic optimization to collision avoidance." In Proceedings of the 2004 American Control Conference. IEEE, 2004. http://dx.doi.org/10.23919/acc.2004.1383888.

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Allaire, Francois Charles Joseph, Mohammed Tarbouchi, Gilles Labonte, and Vincent Roberge. "Real-time UAV path-terrain collision evaluation on FPGA." In 2018 4th International Conference on Optimization and Applications (ICOA). IEEE, 2018. http://dx.doi.org/10.1109/icoa.2018.8370583.

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Abuhamdah, Anmar, and Masri Ayob. "Multi-Neighbourhood Particle Collision Algorithm for solving course timetabling problems." In 2009 2nd Conference on Data Mining and Optimization. IEEE, 2009. http://dx.doi.org/10.1109/dmo.2009.5341917.

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Reports on the topic "Collision optimization"

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Woerner, Kyle. COLREGS-Compliant Autonomous Collision Avoidance Using Multi-Objective Optimization with Interval Programming. Fort Belvoir, VA: Defense Technical Information Center, June 2014. http://dx.doi.org/10.21236/ada609415.

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