RVO_Py_MAS

Python Implementation of Reciprocal Velocity Obstacle (RVO) for Multi-agent Systems

@ARTICLE{8361450,
  author={M. {Guo} and M. M. {Zavlanos}},
  journal={IEEE Transactions on Robotics}, 
  title={Multirobot Data Gathering Under Buffer Constraints and Intermittent Communication}, 
  year={2018},
  volume={34},
  number={4},
  pages={1082-1097},
  doi={10.1109/TRO.2018.2830370}}

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Description

This package contains a plug-and-play Python package for collision-avoidance in multi-agent system, based on reciprocal velocity obstacles (RVO) and hybrid reciprocal velocity obstacles (HRVO).

It has minimal impact on your control objective and requires minimal integration.

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Features

• Takes a 2D workspace with any number of non-overlaping circular or square obstacles
• Any number of dynamic agents with non-zero volume.
• Allow the choice of VO, RVO, HRVO.
• Direct plug-and-play and fully integrate-able with your control objective, i.e., the output velocity is a minimal modification of the desired velocity.

from your_module import compute_desired_V, Update_V
from RVO import RVO_update

# your control objective here 
V_desired = compute_desired_V(X, control_objective, V_max)

# plug in the RVO controller from this package
V = RVO_update(X, V_desired, workspace_model)

# let the robot move
X = Update_X(X, V, step)

• Scalable and fast, see examples below.
• See example.py for test run. [Video1], [Video2]

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References

• Papers on RVO, HRVO
• There are Python bindings of the C++ implementation from the algorithm developers. For my purposes, the formality is too heavy to be integrated into my own project, so I have my own try.
• This package does not depend on the Clearpath geometric package to compute velocity obstacles.

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Discussion

• For very clustered workspace with a large number of robots, you may need to limit the maximal velocity and use very small step size.
• You may add additional constraints in RVO_update such as the change rate of V, the lower bound of V.
• When applying this module to experimental robot control, you may need to set the step size higher due to hardware constraints.
• In most practical experiments, this scheme should still work by limiting the maximal velocity.