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cs.RO2026

Real-Time, Energy-Efficient, Sampling-Based Optimal Control via FPGA Acceleration

Tanmay Desai, Brian Plancher, R. Iris Bahar

Autonomous mobile robots (AMRs), used for search-and-rescue and remote exploration, require fast and robust planning and control schemes. Sampling-based approaches for Model Predic…

cs.RO2025

Robust Geospatial Coordination of Multi-Agent Communications Networks Under Attrition

Jonathan S. Kent, Eliana Stefani, Brian Plancher

Coordinating emergency responses in extreme environments, such as wildfires, requires resilient and high-bandwidth communication backbones. While autonomous aerial swarms can estab…

cs.RO2025

Robust and Efficient Embedded Convex Optimization through First-Order Adaptive Caching

Ishaan Mahajan, Brian Plancher

Recent advances in Model Predictive Control (MPC) leveraging a combination of first-order methods, such as the Alternating Direction Method of Multipliers (ADMM), and offline preco…

cs.RO2025

Set Phasers to Stun: Beaming Power and Control to Mobile Robots with Laser Light

Charles J. Carver, Hadleigh Schwartz, Toma Itagaki +7

We present Phaser, a flexible system that directs narrow-beam laser light to moving robots for concurrent wireless power delivery and communication. We design a semi-automatic cali…

cs.RO2025

pRRTC: GPU-Parallel RRT-Connect for Fast, Consistent, and Low-Cost Motion Planning

Chih H. Huang, Pranav Jadhav, Brian Plancher +1

Sampling-based motion planning algorithms, like the Rapidly-Exploring Random Tree (RRT) and its widely used variant, RRT-Connect, provide efficient solutions for high-dimensional p…