Autonomous aerial swarming in gnss-denied environments with high obstacle density
The compact flocking of relatively localized Un-manned Aerial Vehicles (UAVs) in high
obstacle density areas is discussed in this paper. The presented work tackles realistic …
obstacle density areas is discussed in this paper. The presented work tackles realistic …
[HTML][HTML] Deep reinforcement learning-based model-free path planning and collision avoidance for UAVs: A soft actor–critic with hindsight experience replay approach
MH Lee, J Moon - ICT Express, 2023 - Elsevier
In this paper, we propose a soft actor–critic (SAC) algorithm with hindsight experience replay
(HER), called SACHER, which is a class of deep reinforcement learning (DRL) algorithm …
(HER), called SACHER, which is a class of deep reinforcement learning (DRL) algorithm …
Adaptive robot navigation with collision avoidance subject to 2nd-order uncertain dynamics
This paper considers the problem of robot motion planning in a workspace with obstacles for
systems with uncertain 2nd-order dynamics. In particular, we combine closed form potential …
systems with uncertain 2nd-order dynamics. In particular, we combine closed form potential …
PACNav: a collective navigation approach for UAV swarms deprived of communication and external localization
Abstract This article proposes Persistence Administered Collective Navigation (PACNav) as
an approach for achieving the decentralized collective navigation of unmanned aerial …
an approach for achieving the decentralized collective navigation of unmanned aerial …
Closed-form barrier functions for multi-agent ellipsoidal systems with uncertain lagrangian dynamics
In this letter, we design a decentralized control protocol for the collision avoidance of a multi-
agent system, which is composed of 3-D ellipsoidal agents that obey second-order uncertain …
agent system, which is composed of 3-D ellipsoidal agents that obey second-order uncertain …
[HTML][HTML] Control of cooperative manipulator-endowed systems under high-level tasks and uncertain dynamics
This paper considers the problem of distributed motion-and task-planning of multi-agent and
multi-agent-object systems under temporal-logic-based tasks and uncertain dynamics. We …
multi-agent-object systems under temporal-logic-based tasks and uncertain dynamics. We …
Kdf: Kinodynamic motion planning via geometric sampling-based algorithms and funnel control
We integrate sampling-based planning techniques with funnel-based feedback control to
develop KDF, a new framework for solving the kinodynamic motion-planning problem via …
develop KDF, a new framework for solving the kinodynamic motion-planning problem via …
Deep reinforcement learning-based uav navigation and control: A soft actor-critic with hindsight experience replay approach
MH Lee, J Moon - arxiv preprint arxiv:2106.01016, 2021 - arxiv.org
In this paper, we propose SACHER (soft actor-critic (SAC) with hindsight experience replay
(HER)), which constitutes a class of deep reinforcement learning (DRL) algorithms. SAC is …
(HER)), which constitutes a class of deep reinforcement learning (DRL) algorithms. SAC is …
Mission aware motion planning (MAP) framework with physical and geographical constraints for a swarm of mobile stations
In this paper, we propose a mission aware motion planning (MAP) framework for a swarm of
autonomous unmanned ground vehicles (UGVs) or mobile stations in an uncertain …
autonomous unmanned ground vehicles (UGVs) or mobile stations in an uncertain …
Mobile robot navigation in complex polygonal workspaces using conformal navigation transformations
L Fan, J Liu - arxiv preprint arxiv:2208.09635, 2022 - arxiv.org
This work proposes a novel transformation termed the conformal navigation transformation
to achieve collision-free navigation of a robot in a workspace populated with arbitrary …
to achieve collision-free navigation of a robot in a workspace populated with arbitrary …