Fernando Bello

Soft Robotics · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Fernando Bello trusts

Their strongest outbound trust, strongest first, inferred from their citations.

1. Pieter Abbeel (in Reinforcement Learning)
2. John Schulman (in Reinforcement Learning)

Papers from Fernando Bello's perspective

Ordered by how strongly the researchers Fernando Bello trusts endorse each paper. Same corpus, a different order for every researcher.

1. Trust Region Policy Optimization (International Conference on Machine Learning)
2. Benchmarking Deep Reinforcement Learning for Continuous Control
3. Multilateral surgical pattern cutting in 2D orthotropic gauze with deep reinforcement learning policies for tensioning
4. Evolution of autonomous and semi‐autonomous robotic surgical systems: a review of the literature (The international journal of medical robotics + computer assisted surgery : MRCAS)
5. Design of a Proficiency-Based Skills Training Curriculum for the Fundamentals of Laparoscopic Surgery (Surgical Innovation)
6. Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions
7. Supervised autonomous robotic soft tissue surgery
8. Path Planning for Automation of Surgery Robot based on Probabilistic Roadmap and Reinforcement Learning
9. Towards transferring skills to flexible surgical robots with programming by demonstration and reinforcement learning
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• A New Tensioning Method using Deep Reinforcement Learning for Surgical Pattern Cutting (2019) — 42 citations
• Toward a Common Framework and Database of Materials for Soft Robotics (2020) — 299 citations