# Preemptive Motion Planning for Human-to-Robot Indirect Placement Handovers

arXiv: https://arxiv.org/abs/2203.00156 · HTML: https://mlsanity.com/paper/2203.00156/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 44 references that are in the map.
- First posted on arXiv 1 Mar 2022.

## Builds on (most cited first, 13 of 13)

- [OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields](https://mlsanity.com/paper/1812.08008/) (2018)
- [Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks](https://mlsanity.com/paper/1803.10892/) (2018)
- [Socially Aware Motion Planning with Deep Reinforcement Learning](https://mlsanity.com/paper/1703.08862/) (2017)
- [Understanding Human Gaze Communication by Spatio-Temporal Graph Reasoning](https://mlsanity.com/paper/1909.02144/) (2019)
- [Probabilistic Prediction of Interactive Driving Behavior via Hierarchical Inverse Reinforcement Learning](https://mlsanity.com/paper/1809.02926/) (2018)
- [MoGaze: A Dataset of Full-Body Motions that Includes Workspace Geometry and Eye-Gaze](https://mlsanity.com/paper/2011.11552/) (2020)
- [Human Grasp Classification for Reactive Human-to-Robot Handovers](https://mlsanity.com/paper/2003.06000/) (2020)
- [Anticipation in Human-Robot Cooperation: A Recurrent Neural Network Approach for Multiple Action Sequences Prediction](https://mlsanity.com/paper/1802.10503/) (2018)
- [Communicative Learning with Natural Gestures for Embodied Navigation Agents with Human-in-the-Scene](https://mlsanity.com/paper/2108.02846/) (2021)
- [Estimating Human Intent for Physical Human-Robot Co-Manipulation](https://mlsanity.com/paper/1705.10851/) (2017)
- [Anticipatory Human-Robot Collaboration via Multi-Objective Trajectory Optimization](https://mlsanity.com/paper/2006.03614/) (2020)
- [Anticipating Human Intention for Full-Body Motion Prediction in Object Grasping and Placing Tasks](https://mlsanity.com/paper/2007.10038/) (2020)
- [Supportive Actions for Manipulation in Human-Robot Coworker Teams](https://mlsanity.com/paper/2005.00769/) (2020)

## Built on by (most cited first, 2 of 2)

- [Robots Influencing Humans to Reveal their Goals during Collaboration and Competition](https://mlsanity.com/paper/2609.05519/) (2026)
- [Int3DNet: Scene-Motion Cross Attention Network for 3D Intention Prediction in Mixed Reality](https://mlsanity.com/paper/2603.13355/) (2026)

## Abstract (arXiv)

As technology advances, the need for safe, efficient, and collaborative human-robot-teams has become increasingly important. One of the most fundamental collaborative tasks in any setting is the object handover. Human-to-robot handovers can take either of two approaches: (1) direct hand-to-hand or (2) indirect hand-to-placement-to-pick-up. The latter approach ensures minimal contact between the human and robot but can also result in increased idle time due to having to wait for the object to first be placed down on a surface. To minimize such idle time, the robot must preemptively predict the human intent of where the object will be placed. Furthermore, for the robot to preemptively act in any sort of productive manner, predictions and motion planning must occur in real-time. We introduce a novel prediction-planning pipeline that allows the robot to preemptively move towards the human agent's intended placement location using gaze and gestures as model inputs. In this paper, we investigate the performance and drawbacks of our early intent predictor-planner as well as the practical benefits of using such a pipeline through a human-robot case study.