Differentially constrained mobile robot motion planning in state lattices M Pivtoraiko, RA Knepper, A Kelly Journal of Field Robotics 26 (3), 308-333, 2009 | 583 | 2009 |
DeepMPC: Learning deep latent features for model predictive control. I Lenz, RA Knepper, A Saxena Robotics: Science and Systems 10, 25, 2015 | 409 | 2015 |
Ikeabot: An autonomous multi-robot coordinated furniture assembly system RA Knepper, T Layton, J Romanishin, D Rus 2013 IEEE International conference on robotics and automation, 855-862, 2013 | 256 | 2013 |
RF-compass: Robot object manipulation using RFIDs J Wang, F Adib, R Knepper, D Katabi, D Rus Proceedings of the 19th annual international conference on Mobile computing …, 2013 | 230 | 2013 |
Asking for help using inverse semantics S Tellex, R Knepper, A Li, D Rus, N Roy Robotics: Science and Systems Foundation, 2014 | 212 | 2014 |
A helping hand: Soft orthosis with integrated optical strain sensors and EMG control H Zhao, J Jalving, R Huang, R Knepper, A Ruina, R Shepherd IEEE Robotics & Automation Magazine 23 (3), 55-64, 2016 | 185 | 2016 |
Human expectations of social robots M Kwon, MF Jung, RA Knepper 2016 11th ACM/IEEE international conference on human-robot interaction (HRI …, 2016 | 170 | 2016 |
Herb 2.0: Lessons learned from developing a mobile manipulator for the home SS Srinivasa, D Berenson, M Cakmak, A Collet, MR Dogar, AD Dragan, ... Proceedings of the IEEE 100 (8), 2410-2428, 2012 | 150 | 2012 |
Local motion planning for collaborative multi-robot manipulation of deformable objects J Alonso-Mora, R Knepper, R Siegwart, D Rus 2015 IEEE international conference on robotics and automation (ICRA), 5495-5502, 2015 | 135 | 2015 |
Model-predictive motion planning: Several key developments for autonomous mobile robots T Howard, M Pivtoraiko, RA Knepper, A Kelly IEEE Robotics & Automation Magazine 21 (1), 64-73, 2014 | 126 | 2014 |
Pedestrian-inspired sampling-based multi-robot collision avoidance RA Knepper, D Rus 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human …, 2012 | 104 | 2012 |
Will UML 2.0 be agile or awkward? C Kobryn Communications of the ACM 45 (1), 107-110, 2002 | 103* | 2002 |
High Performance State Lattice Planning Using Heuristic Look-Up Tables. RA Knepper, A Kelly IROS, 3375-3380, 2006 | 98 | 2006 |
Recovering from failure by asking for help RA Knepper, S Tellex, A Li, N Roy, D Rus Autonomous Robots 39, 347-362, 2015 | 94 | 2015 |
Mapping navigation instructions to continuous control actions with position-visitation prediction V Blukis, D Misra, RA Knepper, Y Artzi Conference on Robot Learning, 505-518, 2018 | 87 | 2018 |
Learning to map natural language instructions to physical quadcopter control using simulated flight V Blukis, Y Terme, E Niklasson, RA Knepper, Y Artzi arXiv preprint arXiv:1910.09664, 2019 | 86 | 2019 |
Path and trajectory diversity: Theory and algorithms MS Branicky, RA Knepper, JJ Kuffner 2008 IEEE International Conference on Robotics and Automation, 1359-1364, 2008 | 80 | 2008 |
Implicit communication in a joint action RA Knepper, CI Mavrogiannis, J Proft, C Liang Proceedings of the 2017 acm/ieee international conference on human-robot …, 2017 | 79 | 2017 |
Effects of distinct robot navigation strategies on human behavior in a crowded environment C Mavrogiannis, AM Hutchinson, J Macdonald, P Alves-Oliveira, ... 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI …, 2019 | 77 | 2019 |
Social momentum: A framework for legible navigation in dynamic multi-agent environments CI Mavrogiannis, WB Thomason, RA Knepper Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot …, 2018 | 72 | 2018 |