Experimental Comparison of Global Motion Planning Algorithms for Wheeled Mobile Robots
Planning smooth and energy-efficient motions for wheeled mobile robots is a central task for applications ranging from autonomous …
Scaling simulation-to-real transfer by learning composable robot skills
We present a strategy for simulation-to-real transfer, which builds on recent advances in robot skill decomposition. Rather than …
LAMP: Large-Scale Autonomous Mapping and Positioning for Exploration of Perceptually-Degraded Subterranean Environments
Simultaneous Localization and Mapping (SLAM) in large-scale, unknown, and complex subterranean environments is a challenging problem. …
Automatic Differentiation and Continuous Sensitivity Analysis of Rigid Body Dynamics
A key ingredient to achieving intelligent behavior is physical understanding that equips robots with the ability to reason about the …
Physics-based Simulation of Continuous-Wave LIDAR for Localization, Calibration and Tracking
Light Detection and Ranging (LIDAR) sensors play an important role in the perception stack of autonomous robots, supplying mapping and …
Real2Sim Transfer using Differentiable Physics
Accurate simulations allow modern machine learning techniques to be applied to robotics problems, with sample-collection runtimes …
Interactive Differentiable Simulation
Intelligent agents need a physical understanding of the world to predict the impact of their actions in the future. While …
Confidence-rich Grid Mapping
Representing the environment is a fundamental task in enabling robots to act autonomously in unknown environments. In this work, we …
Simulator Predictive Control: Using Learned Task Representations and MPC for Zero-Shot Generalization and Sequencing
Simulation-to-real transfer is an important strategy for making reinforcement learning practical with real robots. Successful …
Scaling simulation-to-real transfer by learning composable robot skills
We present a novel solution to the problem of simulation-to-real transfer, which builds on recent advances in robot skill …
Heterogeneous Sensor Fusion via Confidence-rich 3D Grid Mapping: Application to Physical Robots
Autonomous navigation of intelligent physical systems largely depend on the ability of the system to generate an accurate map of its …
Gradient-Informed Path Smoothing for Wheeled Mobile Robots
Planning smooth trajectories is important for the safe, efficient and comfortable operation of mobile robots, such as wheeled robots …
Planning High-speed Safe Trajectories in Confidence-rich Maps
Planning safe, high-speed trajectories in unknown environments remains a major roadblock on the way toward achieving fast autonomous …
Confidence-rich Grid Mapping
Occupancy grids are a common framework in robotics for creating a spatial map of the environment. Traditional grid mapping algorithms …
Web Text-based Network Industry Classifications: Preliminary Results
Studies of market structure and product market competition are important in many disciplines, such as economics, finance, accounting …
Concept and Realization of a Diagnostic System for Smart Environments
Automatically diagnosing a complex system containing heterogeneous hard- and software components is a challenging task. To analyze the …
