19 citations · 22 across the 15 of their papers we have counts for
7 papers · 2 filters
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…
GATO: GPU-Accelerated and Batched Trajectory Optimization for Scalable Edge Model Predictive Control
Alexander Du, Emre Adabag, Gabriel Bravo-Palacios +1
While Model Predictive Control (MPC) delivers strong performance across robotics applications, solving the underlying (batches of) nonlinear trajectory optimization (TO) problems o…
HJCD-IK: GPU-Accelerated Inverse Kinematics through Batched Hybrid Jacobian Coordinate Descent
Cael Yasutake, Andrew H. Liu, Zachary Kingston +1
Inverse Kinematics (IK) is a core problem in robotics, in which joint configurations are found to achieve a (collision-free) desired end-effector pose. Modern IK solvers face a fun…
TAG-K: Tail-Averaged Greedy Kaczmarz for Computationally Efficient and Performant Online Inertial Parameter Estimation
Shuo Sha, Anupam Bhakta, Zhenyuan Jiang +4
Accurate online inertial parameter estimation is essential for adaptive robotic control, enabling real-time adjustment to payload changes, environmental interactions, and system we…
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…
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…
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…