Trajectory Planning of Unicycle Mobile Robots With a Trapezoidal-Velocity Constraint

Haddad, Moussa; Khalil, Wisama; Lehtihet, H.E.

doi:10.1109/tro.2010.2062090

Cited by 50 publications

(13 citation statements)

References 33 publications

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“…Solutions A, B and C marked on Figure 3 are the extreme non-dominated solutions, which correspond to the minimum value of f 1 , f 2 and f 3 , respectively. Given the same parameter as Case I, contrastive simulations are performed where joint velocities are determined by conventional trapezoidal-velocity profile (mark as solution T) [30] (acceleration and deceleration time are both set as 30 seconds). The results listed in Table 3 are obtained by computing kinematics according to the four sets of joint trajectories.…”

Section: Resultsmentioning

confidence: 99%

Multi-Objective Trajectory Planning of FFSM Carrying a Heavy Payload

Liu

Jia

Chen

et al. 2015

International Journal of Advanced Robotic Systems

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Aiming at carrying a heavy payload to a desired pose (including position and orientation), a multi-objective optimization-based approach for maximum-payload trajectory planning of free-floating space manipulators (FFSM) is proposed in this paper. The presented approach corresponds to two typical applications: (i) the manipulator joints attain the desired states; (ii) the inertial pose of the end-effector (pose with respect to the inertial frame) attains the desired values, for which a novel two-stage method is presented. Firstly, for the purpose of reducing computational complexity, dynamics equations are derived using a spatial operator algebra (SOA) method. Secondly, objective functions are defined according to the improvement of load-carrying capacity and pose requirements of the endeffector. Then, the joint trajectories are specified using sinusoidal polynomial functions. Finally, a multi-objective particle optimization (MOPSO) algorithm is employed to obtain a non-dominated solution set, during which process particles that do not satisfy the constraints are eliminated. Simulations are performed for a 7-DOF FFSM, considering three and five objectives for optimization in the two applications, respectively. The results demonstrate that the proposed approach can provide satisfactory joint trajectories and improve load-carrying capacity effectively.

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Section: Resultsmentioning

confidence: 99%

Multi-Objective Trajectory Planning of FFSM Carrying a Heavy Payload

Liu

Jia

Chen

et al. 2015

International Journal of Advanced Robotic Systems

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“…Moreover, obstacle avoidance and multi-maneuver parking cannot be treated easily. In Haddad et al (2010), an optimization approach along with trapezoidal velocity constraints simplification solved the trajectory planning problem, and the simulation results showed considerable computation time reduction without losing much quality of the solution. In Li and Shao (2015) and Li et al (2016), the optimal control method is applied to solve the optimal trajectories for autonomous parking.…”

Section: Previous Workmentioning

confidence: 99%

A bilevel optimal motion planning (BOMP) model with application to autonomous parking

Shi

Xiong

Chen

et al. 2019

Int J Intell Robot Appl

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In this paper, we present a bilevel optimal motion planning (BOMP) model for autonomous parking. The BOMP model treats motion planning as an optimal control problem, in which the upper level is designed for vehicle nonlinear dynamics, and the lower level is for geometry collision-free constraints. The significant feature of the BOMP model is that the lower level is a linear programming problem that serves as a constraint for the upper-level problem. That is, an optimal control problem contains an embedded optimization problem as constraints. Traditional optimal control methods cannot solve the BOMP problem directly. Therefore, the modified approximate Karush-Kuhn-Tucker theory is applied to generate a general nonlinear optimal control problem. Then the pseudospectral optimal control method solves the converted problem. Particularly, the lower level is the J 2-function that acts as a distance function between convex polyhedron objects. Polyhedrons can approximate objects in higher precision than spheres or ellipsoids. As a result, a fast high-precision BOMP algorithm for autonomous parking concerning dynamical feasibility and collision-free property is proposed. Simulation results and experiment on Turtlebot3 validate the BOMP model, and demonstrate that the computation speed increases almost two orders of magnitude compared with the area criterion based collision avoidance method. Keywords Autonomous parking • Optimal control • Bilevel optimal motion planning (BOMP) • J 2-function * Youlun Xiong

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“…Recently, we observe fast development of sampling-based motion planners building upon the concept of RRT (Rapidly Random exploring Trees) [11,15,17,20,23,30] and other closely related probabilistic approaches such as [13]. Their controller-driven variants are usually obtained by integration of a specific extend procedure into the planner.…”

Section: Related Workmentioning

confidence: 99%

The VFO-Driven Motion Planning and Feedback Control in Polygonal Worlds for a Unicycle with Bounded Curvature of Motion

Gawron

Michałek

2017

J Intell Robot Syst

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Integrated motion planning and control for the purposes of maneuvering mobile robots under state-and input constraints is a problem of vital practical importance in applications of mobile robots such as autonomous transportation. Those constraints arise naturally in practice due to specifics of robot mechanical construction and the presence of obstacles in motion environment. In contrast to approaches focusing on feedback control design under the assumption of given reference motion or motion planning with neglection of subsequent feedback motion execution, we adopt a controller-driven motion planning paradigm, which has recently gained attention of many researchers. It postulates design of motion planning algorithms dedicated to specific feedback control policies, which compute a sequence of feedback control subtasks instead of classically planned open-loop controls or parametric paths. In this spirit, we propose a motion planning algorithm driven by the VFO (Vector Field Orientation) control law for the waypointfollowing task. Presented analysis of the VFO control law reveals its beneficial properties, which are subsequently utilized to solve a generally nonlinear and non-convex optimal motion planning problem by formulating it as a mixed-integer linear program (MILP). The solution proposed in this paper yields a waypoint sequence, which is designed for execution by application of the VFO control law to drive a robot to a prescribed final configuration under an input constraint imposed by bounded curvature of robot motion and state constraints resulting from a convex decomposition of task space. Satisfaction of these constraints is guaranteed analytically and exactly, i.e., without utilization of numerical approximations. Moreover, for a given discrete set of possible waypoint orientations, the proposed algorithm computes plans optimal w.r.t. given cost functional, which can be any convex linear combination of quantities such as robot path length, curvature of robot motion, distance to imposed state constraints, etc. Furthermore, the planning algorithm exploits the possibility of both forward or backward movement of the robot to allow maneuvering in demanding environments. Generated waypoint sequences are a compact representation of a motion plan, which can be immediately executed with the VFO controller without any additional postprocessing. Validity of the proposed approach has 266 J Intell Robot Syst (2018) 89:265-297 been confirmed by simulation studies and experimental motion execution with a laboratory-scale mobile robot.

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Trajectory Planning of Unicycle Mobile Robots With a Trapezoidal-Velocity Constraint

Cited by 50 publications

References 33 publications

Multi-Objective Trajectory Planning of FFSM Carrying a Heavy Payload

Multi-Objective Trajectory Planning of FFSM Carrying a Heavy Payload

A bilevel optimal motion planning (BOMP) model with application to autonomous parking

The VFO-Driven Motion Planning and Feedback Control in Polygonal Worlds for a Unicycle with Bounded Curvature of Motion

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