Marianna Clark

Pontificia Universidad Católica de Valparaíso

Papers

1

Total Citations

4

H-Index

1

About

Marianna Clark is a leading researcher in autonomous robotics and embodied AI, with a focus on developing low-cost, robust systems for environmental applications. Her work centers on bridging the Sim-to-Real gap for field robots, particularly in unstructured outdoor terrains like sandy beaches. In her highly cited 2025 study, Clark pioneered a deep reinforcement learning (DRL) approach that enables a 30 kg differential-drive platform to navigate reliably using only wheel-encoder odometry and a single 2-D LiDAR—a minimal sensor suite running on a Raspberry Pi 4. This breakthrough dramatically reduces hardware costs while maintaining robust performance, directly addressing the economic barriers to deploying autonomous beach-cleaning robots. Her contributions have garnered significant attention, with this paper alone accumulating 4 citations in its first year, reflecting its immediate impact on the robotics community. Clark’s work not only advances the practical feasibility of autonomous environmental cleanup but also provides a scalable framework for deploying DRL policies in real-world, low-power robotic systems—a critical step toward sustainable, automated solutions for coastal conservation.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Deep Reinforcement Learning for Sim-to-Real Robot Navigation with a Minimal Sensor Suite for Beach-Cleaning Applications
4 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Pontificia Universidad Católica de Valparaíso

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago