# Non-Prehensile Manipulation in Clutter with Human-In-The-Loop

## TL;DR

This paper introduces a human-in-the-loop planning framework for pushing objects in cluttered environments, significantly improving success rates and reducing planning times compared to fully autonomous methods.

## Contribution

It presents a novel approach combining human high-level guidance with randomized planning for non-prehensile manipulation in clutter.

## Key findings

- Higher success rates with minimal human input
- Faster planning times compared to autonomous planners
- Effective in both simulation and real robot experiments

## Abstract

We propose a human-operator guided planning approach to pushing-based manipulation in clutter. Most recent approaches to manipulation in clutter employs randomized planning. The problem, however, remains a challenging one where the planning times are still in the order of tens of seconds or minutes, and the success rates are low for difficult instances of the problem. We build on these control-based randomized planning approaches, but we investigate using them in conjunction with human-operator input. In our framework, the human operator supplies a high-level plan, in the form of an ordered sequence of objects and their approximate goal positions. We present experiments in simulation and on a real robotic setup, where we compare the success rate and planning times of our human-in-the-loop approach with fully autonomous sampling-based planners. We show that with a minimal amount of human input, the low-level planner can solve the problem faster and with higher success rates.