English

QCQP-Tunneling: Ellipsoidal Constrained Agent Navigation

Robotics 2023-02-28 v1 Artificial Intelligence

Abstract

This paper presents a convex-QCQP based novel path planning algorithm named ellipsoidal constrained agent navigation (ECAN), for a challenging problem of online path planning in completely unknown and unseen continuous environments. ECAN plans path for the agent by making a tunnel of overlapping ellipsoids, in an online fashion, through the environment. Convex constraints in the ellipsoid-formation step circumvent collision with the obstacles. The problem of online-tunneling is solved as a convex-QCQP. This paper assumes no constraints on shape of the agent and the obstacles. However, to make the approach clearer, this paper first introduces the framework for a point-mass agent with point-size obstacles. After explaining the underlying principle in drawing an ellipsoid tunnel, the framework is extended to the agent and obstacles having finite area (2d space) and finite-volume (3d-space).

Cite

@article{arxiv.2302.13307,
  title  = {QCQP-Tunneling: Ellipsoidal Constrained Agent Navigation},
  author = {Sanjeev Sharma},
  journal= {arXiv preprint arXiv:2302.13307},
  year   = {2023}
}

Comments

In proceedings of the 2nd IASTED International Conference on Robotics, 2011

R2 v1 2026-06-28T08:49:48.962Z