【讨论】希望和大家一起讨论机器人路径规划问题！

yycgy

有兴趣的话，大家积极发言！
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这是一篇相关的英文资料，希望对大家有帮助！
  
Neural Network Approaches to Dynamic Collision-Free Trajectory Generation
  
Abstract—In this paper, dynamic collision-free trajectory
generation in a nonstationary environment is studied using
biologically inspired neural network approaches. The proposed
neural network is topologically organized, where the dynamics
of each neuron is characterized by a shunting equation or an
additive equation. The state space of the neural network can be
either the Cartesian workspace or the joint space of multi-joint
robot manipulators. There are only local lateral connections
among neurons. The real-time optimal trajectory is generated
through the dynamic activity landscape of the neural network
without explicitly searching over the free space nor the collision
paths, without explicitly optimizing any global cost functions,
without any prior knowledge of the dynamic environment, and
without any learning procedures. Therefore the model algorithm
is computationally efficient. The stability of the neural network
system is guaranteed by the existence of a Lyapunov function
candidate. In addition, this model is not very sensitive to the
model parameters. Several model variations are presented and
the differences are discussed. As examples, the proposed models
are applied to generate collision-free trajectories for a mobile
robot to solve a maze-type of problem, to avoid concave U-shaped
obstacles, to track a moving target and at the same to avoid
varying obstacles, and to generate a trajectory for a two-link
planar robot with two targets. The effectiveness and efficiency of
the proposed approaches are demonstrated through simulation
and comparison studies.

dyjdyj

我对仿人的还比较清楚

燕杰

dyjdyj，能不能说的更详细一些，希望你能积极发言！

yycgy

dyjdyj：
      介绍一下 自己的研究方向和研究内容！