◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Mo Chen

10 papers hereh-index 263.2k citations71 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author4
  • last author4

Across the 9 of 10 papers where every author was matched, so the position is known.

fields
  • cs.RO6
  • math.OC2
  • cs.MA1
  • eess.SY1
same name
  • Mo Chen — 9 papers
  • Mo Chen — 4 papers, h 12
  • Mo Chen — 3 papers
  • Mo Chen — 3 papers, h 4
  • Mo Chen — 3 papers, h 2
  • Mo Chen — 3 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172021
most citedFaSTrack: a Modular Framework for Real-Time Motion Planning and Guaranteed Safe Tracking

80 citations · 82 across the 6 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.RO2019

Generating Robust Supervision for Learning-Based Visual Navigation Using Hamilton-Jacobi Reachability

Anjian Li, Somil Bansal, Georgios Giovanis +3

In Bansal et al. (2019), a novel visual navigation framework that combines learning-based and model-based approaches has been proposed. Specifically, a Convolutional Neural Network…

eess.SY2019

Safe Coverage of Compact Domains For Second Order Dynamical Systems

Juan Chacon, Mo Chen, Razvan C. Fetecau

Autonomous systems operating in close proximity with each other to cover a specified area has many potential applications, but to achieve effective coordination, two key challenges…

math.OC2019

Guaranteed-Safe Approximate Reachability via State Dependency-Based Decomposition

Anjian Li, Mo Chen

Hamilton Jacobi (HJ) Reachability is a formal verification tool widely used in robotic safety analysis. Given a target set as unsafe states, a dynamical system is guaranteed not to…

cs.RO2019

TTR-Based Reward for Reinforcement Learning with Implicit Model Priors

Xubo Lyu, Mo Chen

Model-free reinforcement learning (RL) is a powerful approach for learning control policies directly from high-dimensional state and observation. However, it tends to be data-ineff…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.