Lydia Tapia

University of New Mexico, Texas A&M University, Google (United States)

Papers

24

Total Citations

820

H-Index

13

About

No biography available yet.

Research Focus

Computer science24 · 820 citations
Artificial intelligence23 · 813 citations
Robot21 · 763 citations
Motion planning13 · 614 citations
Reinforcement learning10 · 481 citations
Obstacle8 · 439 citations
Robotics8 · 382 citations
Trajectory3 · 380 citations
Engineering9 · 375 citations
Task (project management)7 · 372 citations
Mathematics13 · 350 citations
Mathematical optimization9 · 309 citations

Key Achievements

13
H-Index
24
Papers
820
Total Citations
34
Avg Citations/Paper
🏆 Most Cited Paper
Hybrid Dynamic Moving Obstacle Avoidance Using a Stochastic Reachable Set-Based Potential Field
169 citations · 2017
📈 Most Prolific Year: 2020 (4 Papers)
🤝 Key Collaborators: 39
🏛 Institutions: University of New Mexico, Texas A&M University, Google (United States)

Top Papers

  1. 1
    Hybrid Dynamic Moving Obstacle Avoidance Using a Stochastic Reachable Set-Based Potential Field
    169 citations · 2017
  2. 2
    Automated aerial suspended cargo delivery through reinforcement learning
    166 citations · 2014
  3. 3
    Learning swing-free trajectories for UAVs with a suspended load
    134 citations · 2013
  4. 4
    A reinforcement learning approach towards autonomous suspended load manipulation using aerial robots
    80 citations · 2013
  5. 5
    Safety, Challenges, and Performance of Motion Planners in Dynamic Environments
    28 citations · 2019
  6. 6
    Continuous action reinforcement learning for control-affine systems with unknown dynamics
    27 citations · 2014
  7. 7
    Aggressive Moving Obstacle Avoidance Using a Stochastic Reachable Set Based Potential Field
    24 citations · 2015
  8. 8
    A Motion Planning Approach to Studying Molecular Motions
    23 citations · 2010
  9. 9
    PRM-RL: Long-range Robotic Navigation Tasks by Combining Reinforcement Learning and Sampling-Based Planning
    23 citations · 2018
  10. 10
    Avoiding moving obstacles with stochastic hybrid dynamics using PEARL: PrEference Appraisal Reinforcement Learning
    19 citations · 2016

Key Collaborators

AFAleksandra Faust13 shared papersHLHao-Tien Lewis Chiang10 shared papersSSSatomi Sugaya5 shared papersNMNick Malone4 shared papersRFRafael Fierro4 shared papersMMMarco Morales3 shared papersIPIvana Palunko3 shared papersMRMohammad Reza Yousefi3 shared papersPJPatricio J. Cruz3 shared papersNMNancy M. Amato2 shared papersNRNathanael Rackley2 shared papersKMKasra Manavi2 shared papersJBJohn Baxter2 shared papersKLKendra Lesser2 shared papersMFMarek Fišer2 shared papersMOMeeko Oishi2 shared papersMSMolly Salman1 shared papersBJBruna Jacobson1 shared papersBBBryan Boyd1 shared papersSASam Adé Jacobs1 shared papers
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