Motion planning is an integral part of each robotic system. It is critical to develop an effective
motion in order to achieve a successful performance. The ability to generate a smooth …

Path planning is one of the most important process on applications such as navigating
autonomous vehicles, computer graphics, game development, robotics, and protein folding …

This article demonstrates that collision detection-intensive applications such as robotic
motion planning may be accelerated by performing collision checks with a machine learning …

Sampling-based methods are widely adopted solutions for robot motion planning. The
methods are straightforward to implement, effective in practice for many robotic systems. It is …

We present a neural network collision checking heuristic, ClearanceNet, and a planning
algorithm, CN-RRT. ClearanceNet learns to predict separation distance (minimum distance …

We present a method for effectively planning the motion trajectory of robots in manufacturing
tasks, the tool paths of which are usually complex and have a large number of discrete time …

Lazy search algorithms can efficiently solve problems where edge evaluation is the
bottleneck in computation, as is the case for robotic motion planning. The optimal algorithm …

We present MLNav, a learning-enhanced path planning framework for safety-critical and
resource-limited systems operating in complex environments, such as rovers navigating on …

A hyper-redundant manipulator (HRM) can flexibly accomplish tasks in narrow spaces.
However, its excessive degrees of freedom pose challenges for path planning. In this letter …

Environmental collision is a challenging issue in human–robot collaboration. This article
proposes a novel fuzzy cluster-based framework for robots to have reactive responses to …