From path to trajectory deformation

Kurniawati, Hanna; Fraichard, Thierry

doi:10.1109/iros.2007.4399235

Cited by 20 publications

(10 citation statements)

References 13 publications

(9 reference statements)

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“…The planner considers the nonholonomic constraints. [9] deals with the deformation of trajectories rather than paths by an explicit consideration of temporal information. The deformation is decomposed into an obstacle avoidance step using repulsive forces and a connectivity maintenance step.…”

Section: Introductionmentioning

confidence: 99%

Efficient trajectory optimization using a sparse model

Rösmann

Feiten

Wösch

et al. 2013

2013 European Conference on Mobile Robots

175

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The "timed elastic band" approach optimizes robot trajectories by subsequent modification of an initial trajectory generated by a global planner. The objectives considered in the trajectory optimization include but are not limited to the overall path length, trajectory execution time, separation from obstacles, passing through intermediate way points and compliance with the robots dynamic, kinematic and geometric constraints. "Timed elastic bands" explicitly consider spatialtemporal aspects of the motion in terms of dynamic constraints such as limited robot velocities and accelerations. The trajectory planning operates in real time such that "timed elastic bands" cope with dynamic obstacles and motion constraints. The "timed elastic band problem" is formulated as a scalarized multi-objective optimization problem. Most objectives are local and relate to only a small subset of parameters as they only depend on a few consecutive robot states. This local structure results in a sparse system matrix, which allows the utilization of fast and efficient optimization techniques such as the open-source framework "g2o" for solving "timed elastic band" problems. The "g2o" sparse system solvers have been successfully applied to VSLAM problems. This contribution describes the application and adaptation of the g2o-framework in the context of trajectory modification with the "timed elastic band". Results from simulations and experiments with a real robot demonstrate that the implementation is robust and computationally efficient.

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Section: Introductionmentioning

confidence: 99%

Efficient trajectory optimization using a sparse model

Rösmann

Feiten

Wösch

et al. 2013

2013 European Conference on Mobile Robots

175

View full text Add to dashboard Cite

show abstract

“…For instance, [15] introduced the elastic bands as a combined planning and control methodology to dynamically deform paths while allowing real time obstacle avoidance. The idea of dynamically deform paths evolved and met important progresses [8], [3] and provided extensions to higher planning instances [5]. Other approaches exist that attempt to increase the planner reliability by embedding realistic simulators on the planner, [11].…”

Section: Introductionmentioning

confidence: 99%

Path optimization for rhombic-like vehicles: An approach based on rigid body dynamics

Fonte¹,

Valente²,

Vale³

et al. 2011

2011 15th International Conference on Advanced Robotics (ICAR)

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Abstract-This paper proposes a new path optimization method to improve feasibility and optimality of rough collisionfree paths provided by global planners. Inspired on the dynamics of rigid bodies, this method redefines the elastic bands framework to explicitly handle vehicle geometric constraints and explore the high maneuvering ability of rhombic vehicles. The proposed method was tested as a post optimization technique on global path solutions planned for a large transporter that will operate in the International Thermonuclear Experimental Reactor (ITER). Presented results show the proficiency of this method on handling feasible and reliable paths in cluttered scenarios such as those in ITER.

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“…Unlike path deformation wherein spatial deformation only takes place, trajectory deformation features both spatial and temporal deformations meaning that the planned velocity of the robotic system can be altered thus permitting to handle gracefully situations such as the one depicted in Figure 1. The first trajectory deformation scheme was proposed by one of the authors in Kurniawati and Fraichard (2007). It operates in two stages (collision avoidance and connectivity maintenance stages) and was geared towards manipulator arms.…”

Section: Introductionmentioning

confidence: 99%

Navigating Dynamic Environments with Trajectory Deformation

Fraichard¹,

Delsart²

2009

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Path deformation is a technique that was introduced to generate robot motion wherein a nominal path, that had been computed beforehand, was continuously deformed on-line in response to unforeseen obstacles. In an effort to improve path deformation, this paper presents a trajectory deformation scheme. The main idea is that by incorporating the time dimension and hence information on the obstacles' future behaviour, quite a number of situations where path deformation would fail can be handled. The trajectory represented as a discrete space-time curve is subject to deformation forces both external (to avoid collision with the obstacles) and internal (to maintain trajectory feasibility and connectivity). The trajectory deformation scheme has been tested successfully on a planar robot with double integrator dynamics moving in dynamic environments.

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From path to trajectory deformation

Cited by 20 publications

References 13 publications

Efficient trajectory optimization using a sparse model

Efficient trajectory optimization using a sparse model

Path optimization for rhombic-like vehicles: An approach based on rigid body dynamics

Navigating Dynamic Environments with Trajectory Deformation

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