5 papers
Anytime Global Tensor Motion Planning
Sai Coumar, An T. Le, Zachary Kingston
Global Tensor Motion Planning (GTMP) solves motion planning with batched tensor operations over a layered multipartite graph. We generalize GTMP so that adjacent-layer edges are re…
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…
Evaluating Machine Learning Approaches for ASCII Art Generation
Sai Coumar, Zachary Kingston
Generating structured ASCII art using computational techniques demands a careful interplay between aesthetic representation and computational precision, requiring models that can e…
Foam: A Tool for Spherical Approximation of Robot Geometry
Sai Coumar, Gilbert Chang, Nihar Kodkani +1
Many applications in robotics require primitive spherical geometry, especially in cases where efficient distance queries are necessary. Manual creation of spherical models is time-…
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…