Geometric reasoning about mechanical assembly
Artificial Intelligence
Two manipulation planning algorithms
WAFR Proceedings of the workshop on Algorithmic foundations of robotics
Studies in hybrid systems: modeling, analysis, and control
Studies in hybrid systems: modeling, analysis, and control
Stable pushing: mechanics, controllability, and planning
International Journal of Robotics Research
Planning for in-hand dextrous manipulation
WAFR '98 Proceedings of the third workshop on the algorithmic foundations of robotics on Robotics : the algorithmic perspective: the algorithmic perspective
Iterative solution of nonlinear equations in several variables
Iterative solution of nonlinear equations in several variables
Level Set Methods for Computation in Hybrid Systems
HSCC '00 Proceedings of the Third International Workshop on Hybrid Systems: Computation and Control
A 2-stages locomotion planner for digital actors
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Reconfiguration planning for modular self-reconfigurable robots
Reconfiguration planning for modular self-reconfigurable robots
Planning Algorithms
Creating High-quality Paths for Motion Planning
International Journal of Robotics Research
Navigation among movable obstacles
Navigation among movable obstacles
A Hybrid Approach to Intricate Motion, Manipulation and Task Planning
International Journal of Robotics Research
Sampling-based finger gaits planning for multifingered robotic hand
Autonomous Robots
Multi-modal Motion Planning in Non-expansive Spaces
International Journal of Robotics Research
Templates for pre-grasp sliding interactions
Robotics and Autonomous Systems
Task-driven posture optimization for virtual characters
EUROSCA'12 Proceedings of the 11th ACM SIGGRAPH / Eurographics conference on Computer Animation
Task-driven posture optimization for virtual characters
Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation
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Robots that perform complex manipulation tasks must be able to generate strategies that make and break contact with the object. This requires reasoning in a motion space with a particular multi-modal structure, in which the state contains both a discrete mode (the contact state) and a continuous configuration (the robot and object poses). In this paper we address multi-modal motion planning in the common setting where the state is high-dimensional, and there are a continuous infinity of modes. We present a highly general algorithm, Random-MMP, that repeatedly attempts mode switches sampled at random. A major theoretical result is that Random-MMP is formally reliable and scalable, and its running time depends on certain properties of the multi-modal structure of the problem that are not explicitly dependent on dimensionality. We apply the planner to a manipulation task on the Honda humanoid robot, where the robot is asked to push an object to a desired location on a cluttered table, and the robot is restricted to switch between walking, reaching, and pushing modes. Experiments in simulation and on the real robot demonstrate that Random-MMP solves problem instances that require several carefully chosen pushes in minutes on a PC.