Collision avoidance for multiple agents with joint utility maximization

@inproceedings{AlonsoMora2013CollisionAF,
  title={Collision avoidance for multiple agents with joint utility maximization},
  author={J. Alonso-Mora and M. Rufli and R. Siegwart and P. Beardsley},
  booktitle={ICRA 2013},
  year={2013}
}
In this paper a centralized method for collision avoidance among multiple agents is presented. It builds on the velocity obstacle (VO) concept and its extensions to arbitrary kino-dynamics and is applicable to heterogeneous groups of agents (with respect to size, kino-dynamics and aggressiveness) moving in 2D and 3D spaces. In addition, both static and dynamic obstacles can be considered in the framework. The method maximizes a joint utility function and is formulated as a mixed-integer… Expand
8 Citations
Collision avoidance for aerial vehicles in multi-agent scenarios
  • 102
  • PDF
Cooperative Collision Avoidance for Nonholonomic Robots
  • 50
  • PDF
Proximal Operators for Multi-Agent Path Planning
  • 13
  • Highly Influenced
  • PDF
A Reactive Method for Collision Avoidance in Industrial Environments
  • 14
Shared control of autonomous vehicles based on velocity space optimization
  • 22
  • PDF
Time scaled collision cone based trajectory optimization approach for reactive planning in dynamic environments
  • 31
  • PDF
SPARTA : Fast global planning of collision-avoiding robot trajectories
  • 2
  • PDF

References

SHOWING 1-9 OF 9 REFERENCES
Collision avoidance method for multiple autonomous mobile agents by implicit cooperation
  • Y. Abe, M. Yoshiki
  • Computer Science
  • Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180)
  • 2001
  • 64
Motion Planning in Dynamic Environments Using Velocity Obstacles
  • 1,360
  • PDF
Reciprocal collision avoidance for multiple car-like robots
  • 103
  • PDF
Generation of collision-free trajectories for a quadrocopter fleet: A sequential convex programming approach
  • 183
  • PDF
Mixed-integer quadratic program trajectory generation for heterogeneous quadrotor teams
  • 198
PLEdestrians: a least-effort approach to crowd simulation
  • 236
  • PDF
Object and animation display with multiple aerial vehicles
  • 17