Achievable push-manipulation for complex passive mobile objects using past experience
Tekin Meriçli,Manuela Veloso,H. Levent Akin +2 more
- pp 71-78
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TLDR
The RRT algorithm is modified in such a way to use the recalled robot and object trajectories as building blocks to generate achievable and collision-free push plans that reliably transport the object to a desired 3 DoF pose.Abstract:
The majority of the methods proposed for the problem of push-manipulation planning and execution deal with objects that have quasi-static properties and primitive geometric shapes, yet they usually use complex physics modeling for the manipulated objects as well as the manipulator. We propose an experience-based approach, where the mobile robot experiments with pushable complex real world objects to observe and memorize their motion characteristics together with the associated uncertainty in response to its various pushing actions. Our approach uses this incrementally-built experience to construct push plans based solely on the objects' predicted future trajectories without a need for object-specific physics or contact modeling. We modify the RRT algorithm in such a way to use the recalled robot and object trajectories as building blocks to generate achievable and collision-free push plans that reliably transport the object to a desired 3 DoF pose. We test our method in a realistic 3D simulation environment as well as in a real-world setup, where a variety of pushable objects with freely rolling caster wheels need to be navigated among obstacles to reach their desired final poses. Our experiments demonstrate safe transportation and successful placement of the objects.read more
Citations
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Proceedings ArticleDOI
Nonprehensile whole arm rearrangement planning on physics manifolds
TL;DR: A randomized kinodynamic planner capable of generating trajectories for full arm manipulation and simultaneous object interaction and the ability to solve more rearrangement by pushing tasks than existing primitive based solutions is demonstrated.
Proceedings ArticleDOI
Kinodynamic randomized rearrangement planning via dynamic transitions between statically stable states
TL;DR: This work presents a fast kinodynamic RRT-planner that uses dynamic nonprehensile actions to rearrange cluttered environments and shows that it can exploit the physical fact that in an environment with friction any object eventually comes to rest to exploit a search on the configuration space rather than the state space.
Journal ArticleDOI
Envisioning the qualitative effects of robot manipulation actions using simulation-based projections
Lars Kunze,Michael Beetz +1 more
TL;DR: By envisioning the outcome of actions before committing to them, a robot is able to reason about physical phenomena and can therefore prevent itself from ending up in unwanted situations.
Journal ArticleDOI
Push-manipulation of complex passive mobile objects using experimentally acquired motion models
TL;DR: This work presents an experience-based push-manipulation approach that enables the robot to acquire experimental models regarding how pushable real world objects with complex 3D structures move in response to various pushing actions and demonstrates the superiority of the achievable planning and execution concept through safe and successful push- manipulation of a variety of passively mobile pushable objects.
Proceedings ArticleDOI
Robotic Cleaning Through Dirt Rearrangement Planning with Learned Transition Models
Sarah Elliott,Maya Cakmak +1 more
TL;DR: This work addresses the problem of enabling a manipulator to move arbitrary amounts and configurations of dirt on a surface to a goal region using a cleaning tool with a set of primitive dirt-oriented tool actions.
References
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Journal ArticleDOI
Real-time obstacle avoidance for manipulators and mobile robots
TL;DR: This paper reformulated the manipulator con trol problem as direct control of manipulator motion in operational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and geometric transformation.
MonographDOI
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Rapidly-exploring random trees : a new tool for path planning
TL;DR: The Rapidly-exploring Random Tree (RRT) as discussed by the authors is a data structure designed for path planning problems with high degrees of freedom and non-holonomic constraints, including dynamics.
Book
Real-time obstacle avoidance for manipulators and mobile robots
TL;DR: This paper reformulated the manipulator control problem as direct control of manipulator motion in operational space-the space in which the task is originally described-rather than as control of the task's corresponding joint space motion obtained only after geometric and kinematic transformation.
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