Fruit-picking robot is an important form of intelligent agricultural machinery and has great impact in smart agriculture.Motion planning for its multi-Degree of Freedoms(DOFs)manipulator is significant to picking effi...Fruit-picking robot is an important form of intelligent agricultural machinery and has great impact in smart agriculture.Motion planning for its multi-Degree of Freedoms(DOFs)manipulator is significant to picking efficiency and fruit quality.However,it is difficult to plan appropriate trajectory for such a complex system.The purpose of this article is to gen-erate smooth trajectories for fruit-picking robot manipulators using shortcuts that are con-strained in velocity,acceleration and jerk.The proposed algorithm smooths the robot motion as a post process to trajectory planning.Given an input jerky path,the algorithm will first convert it into a fully synchronized trajectory,and then attempt to reduce the exe-cution time of this trajectory as much as possible while retaining the kinematic motion constraints.The idea of the proposed method is to build shorter and collision-free short-cuts that replace the intermediate motion between two randomly-picked points on the tra-jectory.Experiments carried on a mobile fruit-picking robot demonstrate that this technique is able to generate smooth and collision-free trajectories for robot manipulators.展开更多
Mobile robot local motion planning is responsible for the fast and smooth obstacle avoidance,which is one of the main indicators for evaluating mobile robots'navigation capabilities.Current methods formulate local...Mobile robot local motion planning is responsible for the fast and smooth obstacle avoidance,which is one of the main indicators for evaluating mobile robots'navigation capabilities.Current methods formulate local motion planning as a unified problem;therefore it cannot satisfy the real-time requirement on the platform with limited computing ability.In order to solve this problem,this paper proposes a fast local motion planning method that can reach a planning frequency of 500 Hz on a low-cost CPU.The proposed method decouples the local motion planning as the front-end path searching and the back-end optimization.The front-end is composed of the environment topology analysis and graph searching.The back-end includes dynamically feasible trajectory generation and optimal trajectory selection.Different from the popular methods,the proposed method decomposes the local motion planning into four sub-modules,each of which aims to solve one problem.Combining four sub-modules,the proposed method can obtain the complete local motion planning algorithm which can fast generate a smooth and collision-free trajectory.The experimental results demonstrate that the proposed method has the ability to obtain the smooth,dynamically feasible and collision-free trajectory and the speed of the planning is fast.展开更多
文摘Fruit-picking robot is an important form of intelligent agricultural machinery and has great impact in smart agriculture.Motion planning for its multi-Degree of Freedoms(DOFs)manipulator is significant to picking efficiency and fruit quality.However,it is difficult to plan appropriate trajectory for such a complex system.The purpose of this article is to gen-erate smooth trajectories for fruit-picking robot manipulators using shortcuts that are con-strained in velocity,acceleration and jerk.The proposed algorithm smooths the robot motion as a post process to trajectory planning.Given an input jerky path,the algorithm will first convert it into a fully synchronized trajectory,and then attempt to reduce the exe-cution time of this trajectory as much as possible while retaining the kinematic motion constraints.The idea of the proposed method is to build shorter and collision-free short-cuts that replace the intermediate motion between two randomly-picked points on the tra-jectory.Experiments carried on a mobile fruit-picking robot demonstrate that this technique is able to generate smooth and collision-free trajectories for robot manipulators.
基金the National Key R&D Program of China (No.2017YFB1301300)。
文摘Mobile robot local motion planning is responsible for the fast and smooth obstacle avoidance,which is one of the main indicators for evaluating mobile robots'navigation capabilities.Current methods formulate local motion planning as a unified problem;therefore it cannot satisfy the real-time requirement on the platform with limited computing ability.In order to solve this problem,this paper proposes a fast local motion planning method that can reach a planning frequency of 500 Hz on a low-cost CPU.The proposed method decouples the local motion planning as the front-end path searching and the back-end optimization.The front-end is composed of the environment topology analysis and graph searching.The back-end includes dynamically feasible trajectory generation and optimal trajectory selection.Different from the popular methods,the proposed method decomposes the local motion planning into four sub-modules,each of which aims to solve one problem.Combining four sub-modules,the proposed method can obtain the complete local motion planning algorithm which can fast generate a smooth and collision-free trajectory.The experimental results demonstrate that the proposed method has the ability to obtain the smooth,dynamically feasible and collision-free trajectory and the speed of the planning is fast.
