Reinforcement learning (RL), particularly its combination with deep neural networks,
referred to as deep RL (DRL), has shown tremendous promise across a wide range of …

Neuromorphic hardware enables fast and power-efficient neural network–based artificial
intelligence that is well suited to solving robotic tasks. Neuromorphic algorithms can be …

First-person view (FPV) drone racing is a televised sport in which professional competitors
pilot high-speed aircraft through a 3D circuit. Each pilot sees the environment from the …

We introduce Rotateit, a system that enables fingertip-based object rotation along multiple
axes by leveraging multimodal sensory inputs. Our system is trained in simulation, where it …

Semantic navigation is necessary to deploy mobile robots in uncontrolled environments
such as homes or hospitals. Many learning-based approaches have been proposed in …

Executing safe and precise flight maneuvers in dynamic high-speed winds is important for
the ongoing commoditization of uninhabited aerial vehicles (UAVs). However, because the …

Neural Radiance Fields (NeRFs) have recently emerged as a powerful paradigm for the
representation of natural, complex 3D scenes. Neural Radiance Fields (NeRFs) represent …

Autonomous, agile quadrotor flight raises fundamental challenges for robotics research in
terms of perception, planning, learning, and control. A versatile and standardized platform is …

The best performing learning algorithms devised for event cameras work by first converting
events into dense representations that are then processed using standard CNNs. However …

Over the last decade, the use of autonomous drone systems for surveying, search and
rescue, or last-mile delivery has increased exponentially. With the rise of these applications …