考虑代理质量的转向行为
我正在模拟机器人上使用网络机器人中纸质转向行为的到达行为，
target_offset = target - position
distance = length (target_offset)
ramped_speed = max_speed * (distance / slowing_distance)
clipped_speed = minimum (ramped_speed, max_speed)
desired_velocity = (clipped_speed / distance) * target_offset
steering = desired_velocity - velocity
我遇到的问题是，如果我给它一个很大的减速距离，它就会起作用，并且机器人会以几毫米的误差到达目标，但是由于减速距离太大，需要很长时间才能到达目的地，当到达最后几厘米时，它的行进速度太慢，需要几秒钟才能稳定下来。如果我给它一个较小的减速距离，它就会开始超越目标并开始像寻找一样。我猜测这是因为公式没有考虑机器人的质量？ desired_velocity 变为 0，但不会施加任何制动力。
I am using the arrive behaviour from the paper steering behaviours in webots on a simulated robot,
target_offset = target - position
distance = length (target_offset)
ramped_speed = max_speed * (distance / slowing_distance)
clipped_speed = minimum (ramped_speed, max_speed)
desired_velocity = (clipped_speed / distance) * target_offset
steering = desired_velocity - velocity
The problem I am experiencing is that if I give it a big slowing distance it works and robots arrives at its target with couple mm of error, however since slowing distance is so big it takes a long time to reach its destination by the time it reaches last couple of cms it is travelling so slow that it takes a couple of seconds to settle. If I give it a smaller slowing distance it begins to overshoot the target and begins acting like seek. I am gussing this is due to the formula not taking into account the mass of the robot? desired_velocity goes to 0 but never applies any breaking force.
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可能您想看看典型的PID控制
质量影响速度，请考虑您之前的速度。
希望有帮助。
may be you want to have a look at the typical PID control
mass affects speed, take your previous speed into consideration.
hope it helps.