In this paper, robot path planning in globally unknown environments is studied. Using the rolling optimization concept in predictive control for reference, a new strategy of path planning for a mobile robot, based on ...In this paper, robot path planning in globally unknown environments is studied. Using the rolling optimization concept in predictive control for reference, a new strategy of path planning for a mobile robot, based on rolling windows, is proposed. The method makes full use of the real-time local environmental information detected by the robot and the on-line path planning is carried on in a rolling style. Optimization and feedback are combined in a reasonable way. The convergence of the planning algorithm is also discussed.展开更多
A new path planning method for mobile robots in globally unknown environment with moving obstacles is pre- sented. With an autoregressive (AR) model to predict the future positions of moving obstacles, and the predict...A new path planning method for mobile robots in globally unknown environment with moving obstacles is pre- sented. With an autoregressive (AR) model to predict the future positions of moving obstacles, and the predicted position taken as the next position of moving obstacles, a motion path in dynamic uncertain environment is planned by means of an on-line real-time path planning technique based on polar coordinates in which the desirable direction angle is taken into consideration as an optimization index. The effectiveness, feasibility, high stability, perfect performance of obstacle avoidance, real-time and optimization capability are demonstrated by simulation examples.展开更多
Rolling planning is an efficient method for path planning in uncertain environment. In this paper, the general principle and algorithm of mobile robot path planning based on rolling windows are studied. The sub-optima...Rolling planning is an efficient method for path planning in uncertain environment. In this paper, the general principle and algorithm of mobile robot path planning based on rolling windows are studied. The sub-optimality of rolling path planning is analyzed in details and explained with a concrete example.展开更多
This paper discusses the path planning and path following control problems of robotic fish.In order to avoid obstacles when robotic fish swim in a complex environment,a path plan-ning method based on beetle swarm opti...This paper discusses the path planning and path following control problems of robotic fish.In order to avoid obstacles when robotic fish swim in a complex environment,a path plan-ning method based on beetle swarm optimization(BSO)algorithm is developed.This method considers the influence of the robotic fish’s volume and motion constraints on the path planning task,which can eliminate the collision risk and meet the constraint of the minimum turning radius when the robotic fish obtains the planned path.In construct-ing the path following controller,a multilayer perception based model predictive control(MPC)is adopted to design the optimal control method,and the objective function of the optimal control is dynamically adjusted according to the path curvature.The simulation results show that this proposed method can effectively overcome the complexity of robotic fish kinematics modelling and adapt well to the reference paths of different curvatures given by the path planner.展开更多
In this paper, we describe an algorithm for predicting future positions and orientation of a moving object in a time-varying environment using an autoregressive model (ARM). No constraint is placed on the obstacles mo...In this paper, we describe an algorithm for predicting future positions and orientation of a moving object in a time-varying environment using an autoregressive model (ARM). No constraint is placed on the obstacles motion. The model addresses prediction of translational and rotational motions. Rotational motion is represented using quaternions rather than Euler representation to improve the algorithm performance and accuracy of the prediction results. Compared to other similar systems, the proposed algorithm has an adaptive capability, which enables it to predict over multiple time-steps rather than fixed ones as reported in other works. Such algorithm can be used in a variety of applications. An important one is its application in the framework of designing reliable navigational systems for autonomous mobile robots and more particularly in building effective trajectory planners. Simulation results show how significantly this model could reduce computational cost.展开更多
In this paper, we study the kinematic mechanism and path planning for a two-caster nonholonomic vehicle (the Essboard) which is a recent variant of skateboard. Different from the most studied Snakeboard, the Essboard ...In this paper, we study the kinematic mechanism and path planning for a two-caster nonholonomic vehicle (the Essboard) which is a recent variant of skateboard. Different from the most studied Snakeboard, the Essboard consists of a torsion bar and two platforms, each of which contains a pedal and a caster. We first investigate the relationship between the tilt angles of the pedals and the wheel directions of the casters. This relationship reveals how to control the wheel directions by adjusting the tilt angles. Next, the rotational radius of the Essboard is derived for a given pair of tilt angles of both pedals. The rotational radius of the Essboard is much different than that of the Snakeboard. Then we develop a path-planning algorithm for the Essboard to move from a start position to the goal, using a series of consecutively connected arcs, which are tangent to each other at the connected points. It is shown from a kinematic point of view that the path planning of the Essboard can be solved by a series of pairs of pedals' tilt angles. Three experiments are conducted to confirm the correctness of the main results. The results in this paper are a foundation for further study of the Essboard.展开更多
基金the National 973 Plan (Grant No. G1998030415) and the National Natural Science Foundation of China (Grant No. 69774004) and the National 863 Program (Grant No. 9805-18).
文摘In this paper, robot path planning in globally unknown environments is studied. Using the rolling optimization concept in predictive control for reference, a new strategy of path planning for a mobile robot, based on rolling windows, is proposed. The method makes full use of the real-time local environmental information detected by the robot and the on-line path planning is carried on in a rolling style. Optimization and feedback are combined in a reasonable way. The convergence of the planning algorithm is also discussed.
文摘A new path planning method for mobile robots in globally unknown environment with moving obstacles is pre- sented. With an autoregressive (AR) model to predict the future positions of moving obstacles, and the predicted position taken as the next position of moving obstacles, a motion path in dynamic uncertain environment is planned by means of an on-line real-time path planning technique based on polar coordinates in which the desirable direction angle is taken into consideration as an optimization index. The effectiveness, feasibility, high stability, perfect performance of obstacle avoidance, real-time and optimization capability are demonstrated by simulation examples.
基金This work was supported by the National 973 Plan (Grant No. G1998030415)the National Natural Science Foundation of China (Grant No. 69934020)the National 863 Program (Grant No. 2001AA422140).
文摘Rolling planning is an efficient method for path planning in uncertain environment. In this paper, the general principle and algorithm of mobile robot path planning based on rolling windows are studied. The sub-optimality of rolling path planning is analyzed in details and explained with a concrete example.
基金This work was supported in part by the National Natural Science Foundation of China under Grant 61903007in part by the National Key Research and Development Program of China under Grant 2019YFD0901000.
文摘This paper discusses the path planning and path following control problems of robotic fish.In order to avoid obstacles when robotic fish swim in a complex environment,a path plan-ning method based on beetle swarm optimization(BSO)algorithm is developed.This method considers the influence of the robotic fish’s volume and motion constraints on the path planning task,which can eliminate the collision risk and meet the constraint of the minimum turning radius when the robotic fish obtains the planned path.In construct-ing the path following controller,a multilayer perception based model predictive control(MPC)is adopted to design the optimal control method,and the objective function of the optimal control is dynamically adjusted according to the path curvature.The simulation results show that this proposed method can effectively overcome the complexity of robotic fish kinematics modelling and adapt well to the reference paths of different curvatures given by the path planner.
文摘In this paper, we describe an algorithm for predicting future positions and orientation of a moving object in a time-varying environment using an autoregressive model (ARM). No constraint is placed on the obstacles motion. The model addresses prediction of translational and rotational motions. Rotational motion is represented using quaternions rather than Euler representation to improve the algorithm performance and accuracy of the prediction results. Compared to other similar systems, the proposed algorithm has an adaptive capability, which enables it to predict over multiple time-steps rather than fixed ones as reported in other works. Such algorithm can be used in a variety of applications. An important one is its application in the framework of designing reliable navigational systems for autonomous mobile robots and more particularly in building effective trajectory planners. Simulation results show how significantly this model could reduce computational cost.
基金supported by the National Natural Science Foundation of China (Grant Nos. 51105012 and 61175079)
文摘In this paper, we study the kinematic mechanism and path planning for a two-caster nonholonomic vehicle (the Essboard) which is a recent variant of skateboard. Different from the most studied Snakeboard, the Essboard consists of a torsion bar and two platforms, each of which contains a pedal and a caster. We first investigate the relationship between the tilt angles of the pedals and the wheel directions of the casters. This relationship reveals how to control the wheel directions by adjusting the tilt angles. Next, the rotational radius of the Essboard is derived for a given pair of tilt angles of both pedals. The rotational radius of the Essboard is much different than that of the Snakeboard. Then we develop a path-planning algorithm for the Essboard to move from a start position to the goal, using a series of consecutively connected arcs, which are tangent to each other at the connected points. It is shown from a kinematic point of view that the path planning of the Essboard can be solved by a series of pairs of pedals' tilt angles. Three experiments are conducted to confirm the correctness of the main results. The results in this paper are a foundation for further study of the Essboard.
