Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Mueller, Mark W."'
A Tactile Feedback Approach to Path Recovery after High-Speed Impacts for Collision-Resilient Drones
Aerial robots are a well-established solution for exploration, monitoring, and inspection, thanks to their superior maneuverability and agility. However, in many environments of interest, they risk crashing and sustaining damage following collisions.
Externí odkaz:
http://arxiv.org/abs/2410.14249
Autor:
Bosio, Carlo, Mueller, Mark W.
The combination of Large Language Models (LLMs), systematic evaluation, and evolutionary algorithms has enabled breakthroughs in combinatorial optimization and scientific discovery. We propose to extend this powerful combination to the control of dyn
Externí odkaz:
http://arxiv.org/abs/2410.05406
We present an autonomous aerial system for safe and efficient through-the-canopy fruit counting. Aerial robot applications in large-scale orchards face significant challenges due to the complexity of fine-tuning flight paths based on orchard layouts,
Externí odkaz:
http://arxiv.org/abs/2409.18293
This paper proposes the ProxFly, a residual deep Reinforcement Learning (RL)-based controller for close proximity quadcopter flight. Specifically, we design a residual module on top of a cascaded controller (denoted as basic controller) to generate h
Externí odkaz:
http://arxiv.org/abs/2409.13193
Autor:
Zhang, Dingqi, Loquercio, Antonio, Tang, Jerry, Wang, Ting-Hao, Malik, Jitendra, Mueller, Mark W.
This paper introduces a learning-based low-level controller for quadcopters, which adaptively controls quadcopters with significant variations in mass, size, and actuator capabilities. Our approach leverages a combination of imitation learning and re
Externí odkaz:
http://arxiv.org/abs/2409.12949
Automated Layout Design and Control of Robust Cooperative Grasped-Load Aerial Transportation Systems
We present a novel approach to cooperative aerial transportation through a team of drones, using optimal control theory and a hierarchical control strategy. We assume the drones are connected to the payload through rigid attachments, essentially tran
Externí odkaz:
http://arxiv.org/abs/2310.07649
We introduce collision-resilient aerial vehicles with icosahedron tensegrity structures, capable of surviving high-speed impacts and resuming operations post-collision. We present a model-based design approach, which guides the selection of the tense
Externí odkaz:
http://arxiv.org/abs/2211.12045
Autor:
Zhang, Dingqi, Loquercio, Antonio, Wu, Xiangyu, Kumar, Ashish, Malik, Jitendra, Mueller, Mark W.
This paper proposes an adaptive near-hover position controller for quadcopters, which can be deployed to quadcopters of very different mass, size and motor constants, and also shows rapid adaptation to unknown disturbances during runtime. The core al
Externí odkaz:
http://arxiv.org/abs/2209.09232
Perception-aware receding horizon trajectory planning for multicopters with visual-inertial odometry
Visual inertial odometry (VIO) is widely used for the state estimation of multicopters, but it may function poorly in environments with few visual features or in overly aggressive flights. In this work, we propose a perception-aware collision avoidan
Externí odkaz:
http://arxiv.org/abs/2204.03134
Tethered quadcopters are used for extended flight operations where the power to the system is provided via a tether connected to an external power source. In this work, we consider a system of multiple quadcopters powered by a single tether. We study
Externí odkaz:
http://arxiv.org/abs/2203.08180