A dynamical model of visually-guided steering, obstacle avoidance, and route selection
A dynamical model of visually-guided steering, obstacle avoidance, and route selection
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DOI：
10.1023/a:1023701300169
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发表时间：
2003-08-01
影响因子：
19.5
通讯作者：
Kaelbling, LP
中科院分区：
文献类型：
--
作者：
Fajen, BR;Warren, WH;Kaelbling, LP
使用一个生物启发的模型，我们展示了如何成功的路线选择，通过一个混乱的环境可以出现在线转向动力学，没有明确的路径规划。该模型来自布朗大学虚拟环境导航实验室（VENLab）的人类行走实验。我们发现，目标和障碍物的行为吸引和排斥的标题，运动的方向，观察员以恒定的速度移动。目标对转弯速率的影响随其与航向的角度增加而增加，随其距离呈指数下降;障碍物的影响随角度和距离呈指数下降。线性组合目标项和障碍项使我们能够根据前进方向附近和前方几米处的障碍物信息来模拟穿过任意复杂场景的路径。我们模拟了各种场景配置的模型，并观察到一般有效的路线，并验证了这种行为的移动的机器人。讨论的重点是动力学模型和其他方法，包括势场模型和显式路径规划之间的比较。因此，有效的路线选择可以在线进行，在简单的环境中作为转向和避障的基本行为的结果。
Using a biologically-inspired model, we show how successful route selection through a cluttered environment can emerge from on-line steering dynamics, without explicit path planning. The model is derived from experiments on human walking performed in the Virtual Environment Navigation Lab (VENLab) at Brown. We find that goals and obstacles behave as attractors and repellors of heading, the direction of locomotion, for an observer moving at a constant speed. The influence of a goal on turning rate increases with its angle from the heading and decreases exponentially with its distance; the influence of an obstacle decreases exponentially with angle and distance. Linearly combining goal and obstacle terms allows us to simulate paths through arbitrarily complex scenes, based on information about obstacles in view near the heading direction and a few meters ahead. We simulated the model on a variety of scene configurations and observed generally efficient routes, and verified this behavior on a mobile robot. Discussion focuses on comparisons between dynamical models and other approaches, including potential field models and explicit path planning. Effective route selection can thus be performed on-line, in simple environments as a consequence of elementary behaviors for steering and obstacle avoidance.