# Grasping a Handful: Sequential Multi-Object Dexterous Grasp Generation

arXiv: https://arxiv.org/abs/2503.22370 · HTML: https://mlsanity.com/paper/2503.22370/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 43 references that are in the map.
- First posted on arXiv 28 Mar 2025.

## Builds on (most cited first, 22 of 22)

- [On the Continuity of Rotation Representations in Neural Networks](https://mlsanity.com/paper/1812.07035/) (2018)
- [Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning](https://mlsanity.com/paper/2108.10470/) (2021)
- [DexGraspNet: A Large-Scale Robotic Dexterous Grasp Dataset for General Objects Based on Simulation](https://mlsanity.com/paper/2210.02697/) (2022)
- [UniDexGrasp: Universal Robotic Dexterous Grasping via Learning Diverse Proposal Generation and Goal-Conditioned Policy](https://mlsanity.com/paper/2303.00938/) (2023)
- [Data-Driven Grasp Synthesis - A Survey](https://mlsanity.com/paper/1309.2660/) (2013)
- [Efficient Learning on Point Clouds with Basis Point Sets](https://mlsanity.com/paper/1908.09186/) (2019)
- [Deep Learning Approaches to Grasp Synthesis: A Review](https://mlsanity.com/paper/2207.02556/) (2022)
- [Synthesizing Diverse and Physically Stable Grasps with Arbitrary Hand Structures using Differentiable Force Closure Estimator](https://mlsanity.com/paper/2104.09194/) (2021)
- [GraspXL: Generating Grasping Motions for Diverse Objects at Scale](https://mlsanity.com/paper/2403.19649/) (2024)
- [GenDexGrasp: Generalizable Dexterous Grasping](https://mlsanity.com/paper/2210.00722/) (2022)
- [DexDiffuser: Generating Dexterous Grasps with Diffusion Models](https://mlsanity.com/paper/2402.02989/) (2024)
- [D(R,O) Grasp: A Unified Representation of Robot and Object Interaction for Cross-Embodiment Dexterous Grasping](https://mlsanity.com/paper/2410.01702/) (2024)
- [RealDex: Towards Human-like Grasping for Robotic Dexterous Hand](https://mlsanity.com/paper/2402.13853/) (2024)
- [Learning Task-Oriented Grasping from Human Activity Datasets](https://mlsanity.com/paper/1910.11669/) (2019)
- [UGG: Unified Generative Grasping](https://mlsanity.com/paper/2311.16917/) (2023)
- [DDGC: Generative Deep Dexterous Grasping in Clutter](https://mlsanity.com/paper/2103.04783/) (2021)
- [BODex: Scalable and Efficient Robotic Dexterous Grasp Synthesis Using Bilevel Optimization](https://mlsanity.com/paper/2412.16490/) (2024)
- [Grasp Multiple Objects with One Hand](https://mlsanity.com/paper/2310.15599/) (2023)
- [Exploiting Kinematic Redundancy for Robotic Grasping of Multiple Objects](https://mlsanity.com/paper/2303.01868/) (2023)
- [Multi-Object Grasping -- Types and Taxonomy](https://mlsanity.com/paper/2205.15276/) (2022)
- [Multi-Object Grasping in the Plane](https://mlsanity.com/paper/2206.00229/) (2022)
- [Sequential Multi-Object Grasping with One Dexterous Hand](https://mlsanity.com/paper/2503.09078/) (2025)

## Built on by (most cited first, 3 of 3)

- [Lightning Grasp: High Performance Procedural Grasp Synthesis with Contact Fields](https://mlsanity.com/paper/2511.07418/) (2025)
- [DexCompose: Reusing Dexterous Policies for Multi-Task Manipulation with a Single Hand](https://mlsanity.com/paper/2606.28323/) (2026)
- [Robustness of Robotic Manipulation: Foundations and Frontiers](https://mlsanity.com/paper/2606.31494/) (2026)

## Abstract (arXiv)

We introduce the sequential multi-object robotic grasp sampling algorithm SeqGrasp that can robustly synthesize stable grasps on diverse objects using the robotic hand's partial Degrees of Freedom (DoF). We use SeqGrasp to construct the large-scale Allegro Hand sequential grasping dataset SeqDataset and use it for training the diffusion-based sequential grasp generator SeqDiffuser. We experimentally evaluate SeqGrasp and SeqDiffuser against the state-of-the-art non-sequential multi-object grasp generation method MultiGrasp in simulation and on a real robot. The experimental results demonstrate that SeqGrasp and SeqDiffuser reach an 8.71%-43.33% higher grasp success rate than MultiGrasp. Furthermore, SeqDiffuser is approximately 1000 times faster at generating grasps than SeqGrasp and MultiGrasp. Project page: https://yulihn.github.io/SeqGrasp/.