The State of Robot Motion Generation

TL;DR

This paper reviews 50 years of robot motion generation methods, comparing explicit and implicit modeling approaches, and discusses current advancements and integration opportunities in the field.

Contribution

It provides a comprehensive survey of diverse methodologies for robot motion generation, highlighting their properties and potential for integration.

Findings

Current state-of-the-art methods vary widely in approach

Opportunities exist for integrating different motion generation techniques

The survey identifies gaps and future directions in robot motion research

Abstract

This paper reviews the large spectrum of methods for generating robot motion proposed over the 50 years of robotics research culminating in recent developments. It crosses the boundaries of methodologies, typically not surveyed together, from those that operate over explicit models to those that learn implicit ones. The paper discusses the current state-of-the-art as well as properties of varying methodologies, highlighting opportunities for integration.