As a fundamental component of autonomous driving systems, motion planning has garnered
significant attention from both academia and industry. This paper focuses on efficient and …

This letter presents a complete framework Meeting-Merging-Mission for multi-robot
exploration under communication restriction. Considering communication is limited in both …

Adaptive autonomous navigation with no prior knowledge of extraneous disturbance is of
great significance for quadrotors in a complex and unknown environment. The mainstream …

This paper presents RAYEN, a framework to impose hard convex constraints on the output
or latent variable of a neural network. RAYEN guarantees that, for any input or any weights …

In this paper, we describe a robust multi-drone planning framework for high-speed
trajectories in large scenes. It uses a free-space-oriented map to free the optimization from …

This paper proposes a method for simultaneously planning a path and a sequence of
deformations for a tensegrity drone. Previous work in the field required the use of bounding …

In general, optimal motion planning can be performed both locally and globally. In such a
planning, the choice in favor of either local or global planning technique mainly depends on …

In recent years, mobile robots are becoming ambitious and deployed in large-scale
scenarios. Serving as a high-level understanding of environments, a sparse skeleton graph …

1) Restrictive Inflation is designed to ensure the managibility of the generated convex
polytope. Based on its characteristic of few variables but rich constraints, an efficient and …

To deploy Unmanned Aerial Vehicles (UAVs) inside heterogeneous GPS-denied confined
(potentially unknown) spaces, such as those encountered in mining and Urban Search and …