The problem of planning for a robot that operates in environments containing a large
number of objects, taking actions to move itself through the world as well as to change the …

Sampling-based motion planning is one of the fundamental paradigms to generate robot
motions, and a cornerstone of robotics research. This comparative review provides an up-to …

This paper presents the development, testing and validation of SWEEPER, a robot for
harvesting sweet pepper fruit in greenhouses. The robotic system includes a six degrees of …

We present iGibson 1.0, a novel simulation environment to develop robotic solutions for
interactive tasks in large-scale realistic scenes. Our environment contains 15 fully interactive …

Motion planning is a fundamental research area in robotics. Sampling-based methods offer
an efficient solution for what is otherwise a rather challenging dilemma of path planning …

The open motion planning library (OMPL) is a new library for sampling-based motion
planning, which contains implementations of many state-of-the-art planning algorithms. The …

In this paper we present a novel probabilistic sampling-based motion planning algorithm
called the Fast Marching Tree algorithm (FMT*). The algorithm is specifically aimed at …

Robots that can move autonomously and can make intelligent decisions by perceiving their
environments and surrounding objects are known as autonomous mobile robots. Such …

Mobile robotics research is an emerging area since last three decades. The present
research on mobile robotics addresses the problems which are mainly on path planning …

Path planning and navigation is a very important problem in robotics, especially for mobile
robots operating in complex environments. Sampling based planners such as the …