irsim.lib.algorithm.rvo

This file is the implementation of the Reciprocal Velocity Obstacle (RVO) algorithm for multi-robot collision avoidance.

Author: Ruihua Han

reference: MengGuo/RVO_Py_MAS

Classes

reciprocal_vel_obs

A class to implement the Reciprocal Velocity Obstacle (RVO) algorithm for multi-robot collision avoidance.

Module Contents

class irsim.lib.algorithm.rvo.reciprocal_vel_obs(state: list, obs_state_list=None, vxmax=1.5, vymax=1.5, acce=0.5, factor=1.0, line_obs_list=None)

A class to implement the Reciprocal Velocity Obstacle (RVO) algorithm for multi-robot collision avoidance.

Parameters:

• state (list) – The rvo state of the agent [x, y, vx, vy, radius, vx_des, vy_des].

• obs_state_list (list) – List of states of static obstacles [[x, y, vx, vy, radius]].

• vxmax (float) – Maximum velocity in the x direction.

• vymax (float) – Maximum velocity in the y direction.

• acce (float) – Acceleration limit.

• factor (float) – Penalty weighting factor for velocity selection.

• line_obs_list (list) – List of line segments [[x1, y1, x2, y2], …].

state

obs_state_list = None

line_obs_list = None

vxmax = 1.5

vymax = 1.5

acce = 0.5

factor = 1.0

update(state, obs_state_list, line_obs_list=None)

cal_vel(mode='rvo')

Calculate the velocity of the agent based on the Reciprocal Velocity Obstacle (RVO) algorithm.

Parameters:

mode (str) – The vo configure to calculate the velocity. It can be “rvo”, “hrvo”, or “vo”. - rvo: Reciprocal Velocity Obstacle (RVO) algorithm, for multi-robot collision avoidance. - hrvo: Hybrid Reciprocal Velocity Obstacle (HRVO) algorithm, for multi-robot collision avoidance. - vo: Velocity Obstacle (VO) algorithm, for obstacle-robot collision avoidance.

Returns:

Selected velocity [vx, vy].

Return type:

list[float]

config_rvo()

config_rvo_mode(obstacle)

config_hrvo()

config_hrvo_mode(obstacle)

config_vo()

config_vo_mode(obstacle)

config_vo_lines()

Compute VO cones for line segment obstacles.

For each segment, compute the angular span as seen from the agent, expanded by asin(r / dist) on each side to account for the agent radius. The apex is [0, 0] since line obstacles are static.

vel_candidate(rvo_list)

vo_out(vx, vy, rvo_list)

vel_select(vo_outside, vo_inside)

penalty(vel, vel_des, factor)

static between_vector(line_left_vector, line_right_vector, line_vector)

static cross_product(vector1, vector2)