Smooth Local Path Planning for Autonomous Vehicles

Kanayama, Yutaka; Hartman, Bruce I.

doi:10.1007/978-1-4613-8997-2_6

Cited by 80 publications

(54 citation statements)

References 1 publication

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“…Nevertheless, other types of continuous curvature curves for mobile robots have been proposed. A different type from the one first considered is the cubic spiral [24]. It is a curve along which the curvature is a cubic function on the arc length.…”

Section: Te(τ ) Dτmentioning

confidence: 99%

An Optimality Principle Governing Human Walking

et al. 2008

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Abstract-In this paper, we investigate different possible strategies underlying the formation of human locomotor trajectories in goal-directed walking. Seven subjects were asked to walk within a motion capture facility from a fixed starting point and direction, and to cross over distant porches for which both position and direction in the room were changed over trials. Stereotyped trajectories were observed in the different subjects. The underlying idea to attack this question has been to relate this problem to an optimal control scheme: the trajectory is chosen according to some optimization principle. This is our basic starting assumption. The subject being viewed as a controlled system, we tried to identify several criteria that could be optimized. Is it the time to perform the trajectory? The length of the path? The minimum jerk along the path?. . . We found that the variation (time derivative) of the curvature of the locomotor paths is minimized. Moreover, we show that the human locomotor trajectories are well approximated by the geodesics of a differential system minimizing the L 2 norm of the control. Such geodesics are made of arcs of clothoids. The clothoid or Cornu spiral is a curve, whose curvature grows with the distance from the origin.

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Section: Te(τ ) Dτmentioning

confidence: 99%

An Optimality Principle Governing Human Walking

et al. 2008

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“…The path curvature and the derivative of path curvature are adopted for the calculating the smoothness [9]. And the angular velocity and the angle difference between the nodes of path are used for considering the smoothness [10].…”

Section: Smoothness Of the Pathmentioning

confidence: 99%

Smooth Path Planning by Fusion of Artificial Potential Field Method and Collision Cone Approach

et al. 2016

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Abstract.A variety of path planning methods have been developed for different purposes, such as minimum path length and minimum processing time and smoothness of the path. This paper presents a novel path planning method by fusion of artificial potential filed (APF) and collision cone approach. The proposed algorithm provides smooth path and avoids local minima problem of the existing APF. And the smoothness of the path produced from the proposed algorithm is estimated by calculating the accumulated force which occurs while a robot passes a whole path. The proposed smooth path planning also can be helpful for considering vehicle kinematics and the safety of vehicle passengers. The simulation results demonstrate the performance of the proposed method.

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“…Most efforts have concentrated on curve-fitting for online planning from line segments (Tsumura et al, 1981) or arcs (Komoriya et al, 1984) or clothoids (Kanayama and Miyake, 1985) or cubic spirals (Kanayama and Hartman, 1988). Curve-fitting relies on identification of the parameters of a vehicle's dynamical model.…”

Section: Fast Dynamics Planning: Recorded Maneuversmentioning

confidence: 99%

A multirange architecture for collision‐free off‐road robot navigation

Sermanet

Hadsell

Scoffier

et al. 2008

Journal of Field Robotics

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We present a multi-layered mapping, planning, and command execution system developed and tested on the LAGR mobile robot. Key to robust performance under uncertainty is the combination of a short-range perception system operating at high frame rate and low resolution and a long-range, adaptive vision system operating at lower frame rate and higher resolution. The short-range module performs local planning and obstacle avoidance with fast reaction times, while the long-range module performs strategic visual planning. Probabilistic traversability labels provided by the perception modules are combined and accumulated into a robot-centered hyperbolic-polar map with a 200 meter effective range. Instead of using a dynamical model of the robot for short-range planning, the system uses a large lookup table of physically-possible trajectory segments recorded on the robot in a wide variety of driving conditions. Localization is performed using a combination of GPS, wheel odometry, IMU, and a high-speed, low-complexity rotational visual odometry module. The end to end system was developed and tested on the LAGR mobile robot, and was verified in independent government tests.

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Smooth Local Path Planning for Autonomous Vehicles

Cited by 80 publications

References 1 publication

An Optimality Principle Governing Human Walking

An Optimality Principle Governing Human Walking

Smooth Path Planning by Fusion of Artificial Potential Field Method and Collision Cone Approach

A multirange architecture for collision‐free off‐road robot navigation

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