On Path Regression with Extreme Learning and the Linear Configuration Space
Author:
Affiliation:
1. Waseda University 3-4-1, Okubo, Shinjuku,Department of Modern Mechanical Engineering,Tokyo,Japan,169-8555
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10023545/10022323/10023622.pdf?arnumber=10023622
Reference30 articles.
1. A New Framework for Joint Trajectory Planning Based on Time-Parameterized B-Splines
2. Neural Path Planning: Fixed Time, Near-Optimal Path Generation via Oracle Imitation
3. Motion Planning Networks: Bridging the Gap Between Learning-Based and Classical Motion Planners
4. Learning Motion Planning Functions using a Linear Transition in the C-space: Networks and Kernels
5. Speeding up deep neural network-based planning of local car maneuvers via efficient B-spline path construction
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