# TriFinger: An Open-Source Robot for Learning Dexterity

arXiv: https://arxiv.org/abs/2008.03596 · HTML: https://mlsanity.com/paper/2008.03596/

## Key facts

- Cited by 31 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Aug 2020.

## Built on by (most cited first, 30 of 31)

- [Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning](https://mlsanity.com/paper/2108.10470/) (2021)
- [Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?](https://mlsanity.com/paper/2303.18240/) (2023)
- [Scaling Proprioceptive-Visual Learning with Heterogeneous Pre-trained Transformers](https://mlsanity.com/paper/2409.20537/) (2024)
- [Weakly supervised causal representation learning](https://mlsanity.com/paper/2203.16437/) (2022)
- [HomeRobot: Open-Vocabulary Mobile Manipulation](https://mlsanity.com/paper/2306.11565/) (2023)
- [Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger](https://mlsanity.com/paper/2108.09779/) (2021)
- [Symmetry Considerations for Learning Task Symmetric Robot Policies](https://mlsanity.com/paper/2403.04359/) (2024)
- [SPA: 3D Spatial-Awareness Enables Effective Embodied Representation](https://mlsanity.com/paper/2410.08208/) (2024)
- [Benchmarking Offline Reinforcement Learning on Real-Robot Hardware](https://mlsanity.com/paper/2307.15690/) (2023)
- [Dexterous Manipulation through Imitation Learning: A Survey](https://mlsanity.com/paper/2504.03515/) (2025)
- [Compositional Multi-Object Reinforcement Learning with Linear Relation Networks](https://mlsanity.com/paper/2201.13388/) (2022)
- [The Role of Pretrained Representations for the OOD Generalization of Reinforcement Learning Agents](https://mlsanity.com/paper/2107.05686/) (2021)
- [MAPLE: Encoding Dexterous Robotic Manipulation Priors Learned From Egocentric Videos](https://mlsanity.com/paper/2504.06084/) (2025)
- [What do we learn from a large-scale study of pre-trained visual representations in sim and real environments?](https://mlsanity.com/paper/2310.02219/) (2023)
- [A soft thumb-sized vision-based sensor with accurate all-round force perception](https://mlsanity.com/paper/2111.05934/) (2021)
- [Rethinking Latent Redundancy in Behavior Cloning: An Information Bottleneck Approach for Robot Manipulation](https://mlsanity.com/paper/2502.02853/) (2025)
- [All the Feels: A dexterous hand with large-area tactile sensing](https://mlsanity.com/paper/2210.15658/) (2022)
- [Improving Behavioural Cloning with Positive Unlabeled Learning](https://mlsanity.com/paper/2301.11734/) (2023)
- [EgoAgent: A Joint Predictive Agent Model in Egocentric Worlds](https://mlsanity.com/paper/2502.05857/) (2025)
- [Learning to Fold Real Garments with One Arm: A Case Study in Cloud-Based Robotics Research](https://mlsanity.com/paper/2204.10297/) (2022)
- [Solving the Real Robot Challenge using Deep Reinforcement Learning](https://mlsanity.com/paper/2109.15233/) (2021)
- [Dexterous Robotic Manipulation using Deep Reinforcement Learning and Knowledge Transfer for Complex Sparse Reward-based Tasks](https://mlsanity.com/paper/2205.09683/) (2022)
- [Morphologically Symmetric Reinforcement Learning for Ambidextrous Bimanual Manipulation](https://mlsanity.com/paper/2505.05287/) (2025)
- [GR-Dexter Technical Report](https://mlsanity.com/paper/2512.24210/) (2025)
- [Grasp and Motion Planning for Dexterous Manipulation for the Real Robot Challenge](https://mlsanity.com/paper/2101.02842/) (2021)
- [Real Robot Challenge 2022: Learning Dexterous Manipulation from Offline Data in the Real World](https://mlsanity.com/paper/2308.07741/) (2023)
- [SpatialBoost: Enhancing Visual Representation through Language-Guided Reasoning](https://mlsanity.com/paper/2603.22057/) (2026)
- [Learning 3D Representations for Spatial Intelligence from Unposed Multi-View Images](https://mlsanity.com/paper/2604.10573/) (2026)
- [Real-World Dexterous Object Manipulation based Deep Reinforcement Learning](https://mlsanity.com/paper/2112.04893/) (2021)
- [Parameter Estimation using Reinforcement Learning Causal Curiosity: Limits and Challenges](https://mlsanity.com/paper/2505.08453/) (2025)

## Abstract (arXiv)

Dexterous object manipulation remains an open problem in robotics, despite the rapid progress in machine learning during the past decade. We argue that a hindrance is the high cost of experimentation on real systems, in terms of both time and money. We address this problem by proposing an open-source robotic platform which can safely operate without human supervision. The hardware is inexpensive (about SI5000[]) yet highly dynamic, robust, and capable of complex interaction with external objects. The software operates at 1-kilohertz and performs safety checks to prevent the hardware from breaking. The easy-to-use front-end (in C++ and Python) is suitable for real-time control as well as deep reinforcement learning. In addition, the software framework is largely robot-agnostic and can hence be used independently of the hardware proposed herein. Finally, we illustrate the potential of the proposed platform through a number of experiments, including real-time optimal control, deep reinforcement learning from scratch, throwing, and writing.