Constraint-Based Motion Planning Using Voronoi Diagrams

Garber, Maxim

doi:10.1007/978-3-540-45058-0_32

Cited by 49 publications

(42 citation statements)

References 3 publications

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“…This design decision makes the algorithm more computationally efficient at the cost of being less effective for highly-articulated robots. Garber and Lin (2004) leverage existing physics-based constrained optimization solving software to move towards the Voronoi Diagram, which can then be traversed by a potential field planner. Rickert et al (2008) espouse a similar planning approach in which overlapping task space bubbles fill the free space.…”

Section: Sampling Strategies With Fixed Biasmentioning

confidence: 99%

Realtime Informed Path Sampling for Motion Planning Search

Knepper

Mason

2016

Springer Tracts in Advanced Robotics

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Mobile robot motions often originate from an uninformed path sampling process such as random or low-dispersion sampling. We demonstrate an alternative approach to path sampling that closes the loop on the expensive collision-testing process. Although all necessary information for collision-testing a path is known to the planner, that information is typically stored in a relatively unavailable form in a costmap or obstacle map. By summarizing the most salient data in a more accessible form, our process delivers a denser sampling of the free path space per unit time than open-loop sampling techniques. We obtain this result by probabilistically modeling-in real time and with minimal information-the locations of obstacles and free space, based on collision-test results. We present CALM, the combined adaptive locality model, along with an algorithm to bias path sampling based on the model's predictions. We provide experimental results in simulation for motion planning on mobile robots, demonstrating up to a 330% increase in paths surviving collision test.

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Section: Sampling Strategies With Fixed Biasmentioning

confidence: 99%

Realtime Informed Path Sampling for Motion Planning Search

Knepper

Mason

2016

Springer Tracts in Advanced Robotics

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“…This method is able to handle problems with thousands of links or thousands of loops. Constrained dynamics enforce constraints such as joint connectivity, spatial relationships, and obstacle avoidance for manipulators up to 6 dof [6]. Other planners require the end effector to traverse a predefined trajectory by generating samples that satisfy the end effector constraints given by the trajectory [30,29].…”

Section: Enforcing Constraints During Samplingmentioning

confidence: 99%

Sampling based motion planning with reachable volumes: Application to manipulators and closed chain systems

McMahon

Thomas

Amato

2014

2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

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We introduce a new concept, reachable volumes, which denotes the set of points that the end effector of a chain or linkage can reach. This generalizes work on reachable distances for planar robots to 3-dimensional spherical joints. We show that the reachable volume of a chain is equivalent to the Minkowski sum of the reachable volumes of its links, which gives us an efficient method for computing reachable volumes. We present a method for generating configurations using reachable volumes for various types of robots including chain robots (with and without closure constraints), tree-like robots, and robots containing a combination of them. Unlike previous methods, ours works for 3-dimensional linkages with spherical joints and is capable of generating samples for problems with constraints on internal joints as well as end effectors. We show that reachable volumes samples are less likely to be invalid due to self-collisions, making reachable volumes sampling more efficient for higher dimensional problems. We also show that these samples are easier to connect than others, resulting in more connected roadmaps. Finally we demonstrate that our method can be applied to 262-dof, multi-loop, and tree-like linkages, problems where existing methods cannot be used (e.g., closed chains with spherical joints) or cannot be solved efficiently (e.g., tree-like robots and high degree of freedom chains with spherical joints).

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“…Maciejewski and Klein where among the first to advocate this technique within a two priority layers architecture [12]. Another early work by Khatib achieves similar results by the use of artificial potential fields [13], whereas a more recent one by Garber and Lin integrates repulsive constraints whose strength is a function of the distance to the obstacle that originates them [14]. The problem with these approaches is that a body part is repulsed from an obstacle even if it is not moving in its direction.…”

Section: Related Workmentioning

confidence: 99%

“…Hybrid path planning techniques exist that use this idea to cope with the complexity of planning in highdimensional configuration spaces, at near real-time rates [18,19]. Garber and Lin apply the same idea to animate a robot arm working in an industrial context [14].…”

Section: Related Workmentioning

confidence: 99%

Environment-Aware Postural Control of Virtual Humans for Real-time Applications

Peinado

Meziat

Boulic

et al. 2006

SAE Technical Paper Series

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Interactive control of a virtual character through full body movement has a wide range of applications. However, there is a need for systems that accurately reproduce the motion of a performer while accounting for surrounding obstacles. We propose an approach based on an efficient Prioritized Inverse Kinematics constraint solver. The inputs to the system are the acquired positions of relevant body parts. These positions are tracked by the virtual character thanks to a set of kinematic constraints. At the same time a special constraint, which we call "observer", is attached to body parts that must be checked for collisions. An observer acts by smoothly damping the motion of its controlled body part towards nearby obstacles, thus preventing future collisions from taking place.

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Constraint-Based Motion Planning Using Voronoi Diagrams

Cited by 49 publications

References 3 publications

Realtime Informed Path Sampling for Motion Planning Search

Realtime Informed Path Sampling for Motion Planning Search

Sampling based motion planning with reachable volumes: Application to manipulators and closed chain systems

Environment-Aware Postural Control of Virtual Humans for Real-time Applications

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