Champion-level drone racing using deep reinforcement learning
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 …
pilot high-speed aircraft through a 3D circuit. Each pilot sees the environment from the …
Autonomous navigation for eVTOL: Review and future perspectives
H Wei, B Lou, Z Zhang, B Liang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
This survey paper explores the emergent domain of electric vertical takeoff and landing
vehicles (eVTOLs), emphasizing the critical role of autonomous navigation capabilities …
vehicles (eVTOLs), emphasizing the critical role of autonomous navigation capabilities …
Recent advances in path integral control for trajectory optimization: An overview in theoretical and algorithmic perspectives
This paper presents a tutorial overview of path integral (PI) approaches for stochastic
optimal control and trajectory optimization. We concisely summarize the theoretical …
optimal control and trajectory optimization. We concisely summarize the theoretical …
Bootstrapping reinforcement learning with imitation for vision-based agile flight
Learning visuomotor policies for agile quadrotor flight presents significant difficulties,
primarily from inefficient policy exploration caused by high-dimensional visual inputs and the …
primarily from inefficient policy exploration caused by high-dimensional visual inputs and the …
Contrastive learning for enhancing robust scene transfer in vision-based agile flight
Scene transfer for vision-based mobile robotics applications is a highly relevant and
challenging problem. The utility of a robot greatly depends on its ability to perform a task in …
challenging problem. The utility of a robot greatly depends on its ability to perform a task in …
TactiGraph: an asynchronous graph neural network for contact angle prediction using neuromorphic vision-based tactile sensing
Vision-based tactile sensors (VBTSs) have become the de facto method for giving robots the
ability to obtain tactile feedback from their environment. Unlike other solutions to tactile …
ability to obtain tactile feedback from their environment. Unlike other solutions to tactile …
A sim-to-real deep learning-based framework for autonomous nano-drone racing
Autonomous drone racing competitions are a proxy to improve unmanned aerial vehicles'
perception, planning, and control skills. The recent emergence of autonomous nano-sized …
perception, planning, and control skills. The recent emergence of autonomous nano-sized …
Environment as policy: Learning to race in unseen tracks
Reinforcement learning (RL) has achieved outstanding success in complex robot control
tasks, such as drone racing, where the RL agents have outperformed human champions in a …
tasks, such as drone racing, where the RL agents have outperformed human champions in a …
Learning Agile Quadrotor Flight in Restricted Environments with Safety Guarantees
With the increasing requirement for agile and efficient controllers in safety-critical scenarios,
controllers that exhibit both agility and safety are attracting attention, especially in the aerial …
controllers that exhibit both agility and safety are attracting attention, especially in the aerial …
Time-Optimal Flight with Safety Constraints and Data-driven Dynamics
Time-optimal quadrotor flight is an extremely challenging problem due to the limited control
authority encountered at the limit of handling. Model Predictive Contouring Control (MPCC) …
authority encountered at the limit of handling. Model Predictive Contouring Control (MPCC) …