{"title":"非线性动力学无人机的轨迹规划与跟踪","authors":"Filip Janecek, Martin Klauco, M. Kvasnica","doi":"10.1109/PC.2017.7976236","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce a Matlab-based toolbox called OPTIPLAN, which is intended to formulate, solve and simulate problems of obstacle avoidance based on model predictive control (MPC). The main goal of the toolbox is that it allows the users to simply set up even complex control problems without loss in efficiency only in few lines of code. Slow mathematical and technical details are fully automated allowing researchers to focus on problem formulation. It can easily perform MPC based closed-loop simulations followed by fetching visualizations of the results. From the theoretical point of view, non-convex obstacle avoidance constraints are tackled in two ways in OPTIPLAN: either by solving mixed-integer program using binary variables, or using time-varying constraints, which leads to a suboptimal solution, but the problem remains convex.","PeriodicalId":377619,"journal":{"name":"2017 21st International Conference on Process Control (PC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Trajectory planning and following for UAVs with nonlinear dynamics\",\"authors\":\"Filip Janecek, Martin Klauco, M. Kvasnica\",\"doi\":\"10.1109/PC.2017.7976236\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduce a Matlab-based toolbox called OPTIPLAN, which is intended to formulate, solve and simulate problems of obstacle avoidance based on model predictive control (MPC). The main goal of the toolbox is that it allows the users to simply set up even complex control problems without loss in efficiency only in few lines of code. Slow mathematical and technical details are fully automated allowing researchers to focus on problem formulation. It can easily perform MPC based closed-loop simulations followed by fetching visualizations of the results. From the theoretical point of view, non-convex obstacle avoidance constraints are tackled in two ways in OPTIPLAN: either by solving mixed-integer program using binary variables, or using time-varying constraints, which leads to a suboptimal solution, but the problem remains convex.\",\"PeriodicalId\":377619,\"journal\":{\"name\":\"2017 21st International Conference on Process Control (PC)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 21st International Conference on Process Control (PC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PC.2017.7976236\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 21st International Conference on Process Control (PC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PC.2017.7976236","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Trajectory planning and following for UAVs with nonlinear dynamics
In this paper, we introduce a Matlab-based toolbox called OPTIPLAN, which is intended to formulate, solve and simulate problems of obstacle avoidance based on model predictive control (MPC). The main goal of the toolbox is that it allows the users to simply set up even complex control problems without loss in efficiency only in few lines of code. Slow mathematical and technical details are fully automated allowing researchers to focus on problem formulation. It can easily perform MPC based closed-loop simulations followed by fetching visualizations of the results. From the theoretical point of view, non-convex obstacle avoidance constraints are tackled in two ways in OPTIPLAN: either by solving mixed-integer program using binary variables, or using time-varying constraints, which leads to a suboptimal solution, but the problem remains convex.