ACM Transactions on Graphics (TOG)
Situation-dependent learning for interleaved planning and robot execution
Situation-dependent learning for interleaved planning and robot execution
Keypoint Recognition Using Randomized Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
Planning Algorithms
Robotic Grasping of Novel Objects using Vision
International Journal of Robotics Research
Learning Local Objective Functions for Robust Face Model Fitting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Towards 3D Point cloud based object maps for household environments
Robotics and Autonomous Systems
Compact models of human reaching motions for robotic control in everyday manipulation tasks
DEVLRN '09 Proceedings of the 2009 IEEE 8th International Conference on Development and Learning
Refining the execution of abstract actions with learned action models
Journal of Artificial Intelligence Research
Probabilistic mobile manipulation in dynamic environments, with application to opening doors
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Learning forward models for robots
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Manipulation planning with workspace goal regions
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
3D model selection from an internet database for robotic vision
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
On Learning, Representing, and Generalizing a Task in a Humanoid Robot
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Action-related place-based mobile manipulation
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Towards performing everyday manipulation activities
Robotics and Autonomous Systems
Learning and reasoning with action-related places for robust mobile manipulation
Journal of Artificial Intelligence Research
Legibility and predictability of robot motion
Proceedings of the 8th ACM/IEEE international conference on Human-robot interaction
Familiarization to robot motion
Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction
Hi-index | 0.00 |
This article investigates methods for achieving more general manipulation capabilities for mobile manipulation platforms, which produce legible behavior in human living environments. To achieve generality and legibility, we combine two control mechanisms. First of all, experience- and observation-based learning of skills is applied to routine tasks, so that the repetitive and stereotypical character of everyday activity is exploited. Second, we use planning, reasoning, and search for novel tasks which have no stereotypical solution. We apply these ideas to the learning and use of action-related places, to the model-based visual recognition and localization of objects, and the learning and application of reaching strategies and motions from humans. We demonstrate the integration of these mechanisms into a single low-level control system for autonomous manipulation platforms.