Reliable and efficient trajectory generation methods are a fundamental need for
autonomous dynamical systems. The goal of this article is to provide a comprehensive …

In the context of robotics and automation, learning from demonstration (LfD) is the paradigm
in which robots acquire new skills by learning to imitate an expert. The choice of LfD over …

Multi-objective optimization problems are ubiquitous in robotics, eg, the optimization of a
robot manipulation task requires a joint consideration of grasp pose configurations …

From quadrotors delivering packages in urban areas to robot arms moving in confined
warehouses, motion planning around obstacles is a core challenge in modern robotics …

In this letter, we propose a robust and efficient quadrotor motion planning system for fast
flight in three-dimensional complex environments. We adopt a kinodynamic path searching …

Gradient-based planners are widely used for quadrotor local planning, in which a Euclidean
Signed Distance Field (ESDF) is crucial for evaluating gradient magnitude and direction …

Space exploration and exploitation depend on the development of on-orbit robotic
capabilities for tasks such as servicing of satellites, removing of orbital debris, or …

We present RoboGen, a generative robotic agent that automatically learns diverse robotic
skills at scale via generative simulation. RoboGen leverages the latest advancements in …

Learning priors on trajectory distributions can help accelerate robot motion planning
optimization. Given previously successful plans, learning trajectory generative models as …

Robot assistants and professional coworkers are becoming a commodity in domestic and
industrial settings. In order to enable robots to share their workspace with humans and …