We present PRM-RL, a hierarchical method for long-range navigation task completion that
combines sampling-based path planning with reinforcement learning (RL). The RL agents …

Integrating task and motion planning is becoming increasingly important due to the
recognition that a growing number of robotics applications in navigation, search-and-rescue …

Motion planning is a fundamental problem in robotics that has motivated research since
more than three decades ago. A large variety of algorithms have been proposed to compute …

Long-range indoor navigation requires guiding robots with noisy sensors and controls
through cluttered environments along paths that span a variety of buildings. We achieve this …

This paper presents a new motion planner, Search Tree with Resolution Independent
Density Estimation (STRIDE), designed for rapid exploration and path planning in high …

This paper presents a motion planner, termed Guided Sampling Tree (GUST), geared
toward mobile robots with nonlinear dynamics and nonholonomic constraints operating in …

Proteins are macromolecules in perpetual motion, switching between structural states to
modulate their function. A detailed characterization of the precise yet complex relationship …

The motion planning is a difficult problem but nevertheless, a crucial part of robotics. The
probabilistic roadmap planners have shown to be an efficient way to solve these planning …

Proteins often undergo slow structural rearrangements that involve several angstroms and
surpass the nanosecond timescale. These spatiotemporal scales challenge physics-based …

Precious information on protein function can be extracted from a detailed characterization of
protein equilibrium dynamics. This remains elusive in wet and dry laboratories, as function …