Edward Schmerling
Edward Schmerling
Verified email at stanford.edu - Homepage
Title
Cited by
Cited by
Year
Fast marching tree: A fast marching sampling-based method for optimal motion planning in many dimensions
L Janson, E Schmerling, A Clark, M Pavone
The International journal of robotics research 34 (7), 883-921, 2015
3622015
Multimodal probabilistic model-based planning for human-robot interaction
E Schmerling, K Leung, W Vollprecht, M Pavone
2018 IEEE International Conference on Robotics and Automation (ICRA), 3399-3406, 2018
922018
Optimal sampling-based motion planning under differential constraints: the driftless case
E Schmerling, L Janson, M Pavone
2015 IEEE International Conference on Robotics and Automation (ICRA), 2368-2375, 2015
672015
Monte Carlo motion planning for robot trajectory optimization under uncertainty
L Janson, E Schmerling, M Pavone
Robotics Research, 343-361, 2018
622018
A convex optimization approach to smooth trajectories for motion planning with car-like robots
Z Zhu, E Schmerling, M Pavone
2015 54th IEEE conference on decision and control (CDC), 835-842, 2015
502015
Optimal sampling-based motion planning under differential constraints: the drift case with linear affine dynamics
E Schmerling, L Janson, M Pavone
2015 54th IEEE Conference on Decision and Control (CDC), 2574-2581, 2015
442015
An asymptotically-optimal sampling-based algorithm for bi-directional motion planning
JA Starek, JV Gomez, E Schmerling, L Janson, L Moreno, M Pavone
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015
342015
Generative modeling of multimodal multi-human behavior
B Ivanovic, E Schmerling, K Leung, M Pavone
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018
272018
On infusing reachability-based safety assurance within probabilistic planning frameworks for human-robot vehicle interactions
K Leung, E Schmerling, M Chen, J Talbot, JC Gerdes, M Pavone
International Symposium on Experimental Robotics, 561-574, 2018
242018
Fast, safe, propellant-efficient spacecraft motion planning under Clohessy–Wiltshire–Hill dynamics
JA Starek, E Schmerling, GD Maher, BW Barbee, M Pavone
Journal of Guidance, Control, and Dynamics 40 (2), 418-438, 2017
232017
Fast, safe, propellant-efficient spacecraft motion planning under Clohessy–Wiltshire–Hill dynamics
JA Starek, E Schmerling, GD Maher, BW Barbee, M Pavone
Journal of Guidance, Control, and Dynamics 40 (2), 418-438, 2017
232017
Evaluating trajectory collision probability through adaptive importance sampling for safe motion planning
E Schmerling, M Pavone
arXiv preprint arXiv:1609.05399, 2016
232016
Real-time stochastic kinodynamic motion planning via multiobjective search on GPUs
B Ichter, E Schmerling, A Agha-mohammadi, M Pavone
2017 IEEE International Conference on Robotics and Automation (ICRA), 5019-5026, 2017
222017
Bidirectional fast marching trees: An optimal sampling-based algorithm for bidirectional motion planning
J Starek, E Schmerling, L Janson, M Pavone
Workshop on Algorithmic Foundations of Robotics, 2014
182014
Real-time, propellant-optimized spacecraft motion planning under Clohessy-Wiltshire-Hill dynamics
JA Starek, E Schmerling, GD Maher, BW Barbee, M Pavone
2016 IEEE Aerospace Conference, 1-16, 2016
162016
On infusing reachability-based safety assurance within planning frameworks for human–robot vehicle interactions
K Leung, E Schmerling, M Zhang, M Chen, J Talbot, JC Gerdes, ...
The International Journal of Robotics Research 39 (10-11), 1326-1345, 2020
142020
Learned critical probabilistic roadmaps for robotic motion planning
B Ichter, E Schmerling, TWE Lee, A Faust
2020 IEEE International Conference on Robotics and Automation (ICRA), 9535-9541, 2020
132020
Revisiting the asymptotic optimality of RRT
K Solovey, L Janson, E Schmerling, E Frazzoli, M Pavone
2020 IEEE International Conference on Robotics and Automation (ICRA), 2189-2195, 2020
112020
Group Marching Tree: Sampling-based approximately optimal motion planning on GPUs
B Ichter, E Schmerling, M Pavone
2017 First IEEE International Conference on Robotic Computing (IRC), 219-226, 2017
102017
Multimodal deep generative models for trajectory prediction: A conditional variational autoencoder approach
B Ivanovic, K Leung, E Schmerling, M Pavone
IEEE Robotics and Automation Letters 6 (2), 295-302, 2020
62020
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Articles 1–20