Abstract： There is a high demand for unmanned aerial vehicle （UAV） flight stability when using vi- sion as a detection method for navigation control. To meet such demand, a new path planning meth- od for controllin...Abstract： There is a high demand for unmanned aerial vehicle （UAV） flight stability when using vi- sion as a detection method for navigation control. To meet such demand, a new path planning meth- od for controlling multi-UAVs is studied to reach multi-waypoints simultaneously under the view of visual navigation technology. A model based on the stable-shortest pythagorean-hodograph （PH） curve is established, which could not only satisfy the demands of visual navigation and control law, but also be easy to compute. Based on the model, a planning algorithm to guide multi-UAVs to reach multi-waypoints at the same time without collisions is developed. The simulation results show that the paths have shorter distance and smaller curvature than traditional methods, which could help to avoid collisions.展开更多
Multi-waypoint planning is essential for manipulators to execute complex tasks efficiently.It requires the manipulator to swiftly traverse designated waypoints while adhering to all the kinematic constraints.However,p...Multi-waypoint planning is essential for manipulators to execute complex tasks efficiently.It requires the manipulator to swiftly traverse designated waypoints while adhering to all the kinematic constraints.However,previous research has not fully exploited the kinematic capabilities of manipulators and has overlooked collision considerations.To address these problems,this paper presents two novel methods called recursive intermediate state optimization(RISO)and overall intermediate state optimization(OISO).RISO decomposes the multi-waypoint planning problem into a sequence of one-waypoint planning tasks,employing a recursive approach to generate feasible solutions efficiently.OISO utilizes an improved whale optimization algorithm(WOA),incorporating multiple iterative processes to perform secondary optimization in high-dimensional space based on the initial value,yielding better solutions.The proposed methods have been validated on a six-degree-of-freedom manipulator platform and compared with several traditional algorithms,as well as the state-of-the-art algorithm,Ruckig.The results show that RISO outperforms Ruckig in scenarios where computation time is critical,while OISO is better suited for scenarios where trajectory quality is prioritized over time.Furthermore,the proposed methods can also handle collisions,ensuring the generation of collision-free trajectories.展开更多
The reentry trajectory optimization for hypersonic vehicle（HV）is a current problem of great interest.Some complex constraints,such as waypoints for reconnaissance and no-fly zones for threat avoidance,are inevitably...The reentry trajectory optimization for hypersonic vehicle（HV）is a current problem of great interest.Some complex constraints,such as waypoints for reconnaissance and no-fly zones for threat avoidance,are inevitably involved in a global strike mission.Of the many direct methods,Gauss pseudospectral method（GPM）has been demonstrated as an effective tool to solve the trajectory optimization problem with typical constraints.However,a series of diffculties arises for complex constraints,such as the uncertainty of passage time for waypoints and the inaccuracy of approximate trajectory near no-fly zones.The research herein proposes a multi-phase technique based on the GPM to generate an optimal reentry trajectory for HV satisfying waypoint and nofly zone constraints.Three kinds of specifc breaks are introduced to divide the full trajectory into multiple phases.The continuity conditions are presented to ensure a smooth connection between each pair of phases.Numerical examples for reentry trajectory optimization in free-space flight and with complex constraints are used to demonstrate the proposed technique.Simulation results show the feasible application of multi-phase technique in reentry trajectory optimization with waypoint and no-fly zone constraints.展开更多
文摘Abstract： There is a high demand for unmanned aerial vehicle （UAV） flight stability when using vi- sion as a detection method for navigation control. To meet such demand, a new path planning meth- od for controlling multi-UAVs is studied to reach multi-waypoints simultaneously under the view of visual navigation technology. A model based on the stable-shortest pythagorean-hodograph （PH） curve is established, which could not only satisfy the demands of visual navigation and control law, but also be easy to compute. Based on the model, a planning algorithm to guide multi-UAVs to reach multi-waypoints at the same time without collisions is developed. The simulation results show that the paths have shorter distance and smaller curvature than traditional methods, which could help to avoid collisions.
基金supported by the Major Science and Technology Projects for Self-Innovation of FAW(Grant No.20210301032GX)。
文摘Multi-waypoint planning is essential for manipulators to execute complex tasks efficiently.It requires the manipulator to swiftly traverse designated waypoints while adhering to all the kinematic constraints.However,previous research has not fully exploited the kinematic capabilities of manipulators and has overlooked collision considerations.To address these problems,this paper presents two novel methods called recursive intermediate state optimization(RISO)and overall intermediate state optimization(OISO).RISO decomposes the multi-waypoint planning problem into a sequence of one-waypoint planning tasks,employing a recursive approach to generate feasible solutions efficiently.OISO utilizes an improved whale optimization algorithm(WOA),incorporating multiple iterative processes to perform secondary optimization in high-dimensional space based on the initial value,yielding better solutions.The proposed methods have been validated on a six-degree-of-freedom manipulator platform and compared with several traditional algorithms,as well as the state-of-the-art algorithm,Ruckig.The results show that RISO outperforms Ruckig in scenarios where computation time is critical,while OISO is better suited for scenarios where trajectory quality is prioritized over time.Furthermore,the proposed methods can also handle collisions,ensuring the generation of collision-free trajectories.
基金supported by Aviation Science Foundation of China(No.2011ZC13001 and 2013ZA18001)National Natural Science Foundation of China(Nos:60975073,61273349,61175109 and 61203223)Innovation Foundation of BUAA for PhD Graduates
文摘The reentry trajectory optimization for hypersonic vehicle（HV）is a current problem of great interest.Some complex constraints,such as waypoints for reconnaissance and no-fly zones for threat avoidance,are inevitably involved in a global strike mission.Of the many direct methods,Gauss pseudospectral method（GPM）has been demonstrated as an effective tool to solve the trajectory optimization problem with typical constraints.However,a series of diffculties arises for complex constraints,such as the uncertainty of passage time for waypoints and the inaccuracy of approximate trajectory near no-fly zones.The research herein proposes a multi-phase technique based on the GPM to generate an optimal reentry trajectory for HV satisfying waypoint and nofly zone constraints.Three kinds of specifc breaks are introduced to divide the full trajectory into multiple phases.The continuity conditions are presented to ensure a smooth connection between each pair of phases.Numerical examples for reentry trajectory optimization in free-space flight and with complex constraints are used to demonstrate the proposed technique.Simulation results show the feasible application of multi-phase technique in reentry trajectory optimization with waypoint and no-fly zone constraints.
