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 …

One of the fundamental fields of research is motion planning. Mobile manipulators present a
unique set of challenges for the planning algorithms, as they are usually kinematically …

Motivated by the substantial achievements of Large Language Models (LLMs) in the field of
natural language processing, recent research has commenced investigations into the …

Large Language Models (LLMs) have been shown to be capable of performing high-level
planning for long-horizon robotics tasks, yet existing methods require access to a pre …

In this paper, we present CHOMP (covariant Hamiltonian optimization for motion planning),
a method for trajectory optimization invariant to reparametrization. CHOMP uses functional …

This paper describes a vision‐based obstacle detection and navigation system for use as
part of a robotic solution for the sustainable intensification of broad‐acre agriculture. To be …

The construction of large structures is one of the main development trends of the space
exploration in the future, such as large space stations, large space solar power stations, and …

Rearranging multiple objects is a critical skill for robots so that they can effectively deal with
clutter in human spaces. This is a challenging problem as it involves combinatorially large …

We consider the problem of learning preferences over trajectories for mobile manipulators
such as personal robots and assembly line robots. The preferences we learn are more …

We consider the problem of learning good trajectories for manipulation tasks. This is
challenging because the criterion defining a good trajectory varies with users, tasks and …