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38
On Delaying Collision Checking in PRM Planning -- Application To Multi-Robot Coordination
- INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
, 2002
"... This paper describes the foundations and algorithms of a new probabilistic roadmap (PRM) planner that is: single-query -- instead of pre-computing a roadmap covering the entire free space, it uses the two input query configurations to explore as little space as possible; bi-directional -- it explo ..."
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Cited by 81 (15 self)
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This paper describes the foundations and algorithms of a new probabilistic roadmap (PRM) planner that is: single-query -- instead of pre-computing a roadmap covering the entire free space, it uses the two input query configurations to explore as little space as possible; bi-directional -- it explores the robot's free space by building a roadmap made of two trees rooted at the query configurations; and lazy in checking collisions -- it delays collision tests along the edges of the roadmap until they are absolutely needed. Several observations motivated this strategy: (1) PRM planners spend a large fraction of their time testing connections for collision; (2) most connections in a roadmap are not on the final path; (3) the collision test for a connection is most expensive when there is no collision; and (4) any short connection between two collision-free configurations has high prior probability of being collision-free. The strengths of single-query and bi-directional sampling techniques, and those of delayed collision checking reinforce each other. Experimental results
A Framework for Using the Workspace Medial Axis in PRM Planners
, 2000
"... Probabilistic roadmap planners have been very successful in path planning for a wide variety of problems, especially applications involving robots with many degrees of freedom. These planners randomly sample the configuration space, building up a roadmap that connects the samples. A major problem is ..."
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Cited by 76 (4 self)
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Probabilistic roadmap planners have been very successful in path planning for a wide variety of problems, especially applications involving robots with many degrees of freedom. These planners randomly sample the configuration space, building up a roadmap that connects the samples. A major problem is finding valid configurations in tight areas, and many methods have been proposed to more effectively sample these regions. By constructing a skeleton-like subset of the free regions of the workspace, these heuristics can be strengthened. The skeleton provides a concise description of the workspace topology and an efficient means of finding points with maximal clearance from the obstacles. We examine the medial axis as a skeleton, including a method to compute an approximation to it. The medial axis is a twoequidistant surface in the workspace. We form a heuristic for finding difficult configurations using the medial axis, and demonstrate its effectiveness in a planner for rigid objects in a three dimensional workspace.
A comparative study of probabilistic roadmap planners
- IN: WORKSHOP ON THE ALGORITHMIC FOUNDATIONS OF ROBOTICS
, 2002
"... The probabilistic roadmap approach is one of the leading motion planning techniques. Over the past eight years the technique has been studied by many different researchers. This has led to a large number of variants of the approach, each with its own merits. It is difficult to compare the different ..."
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Cited by 69 (10 self)
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The probabilistic roadmap approach is one of the leading motion planning techniques. Over the past eight years the technique has been studied by many different researchers. This has led to a large number of variants of the approach, each with its own merits. It is difficult to compare the different techniques because they were tested on different types of scenes, using different underlying libraries, implemented by different people on different machines. In this paper we provide a comparative study of a number of these techniques, all implemented in a single system and run on the same test scenes and on the same computer. In particular we compare collision checking techniques, basic sampling techniques, and node adding techniques. The results should help future users of the probabilistic roadmap planning approach to choose the correct techniques.
Toward Real-Time Path Planning in Changing Environments
, 2000
"... We present a new method for generating collisionfree paths for robots operating in changing environments. Our approach is closely related to recent probabilistic roadmap approaches. These planners use preprocessing and query stages, and are aimed at planning many times in the same environment. In co ..."
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Cited by 68 (4 self)
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We present a new method for generating collisionfree paths for robots operating in changing environments. Our approach is closely related to recent probabilistic roadmap approaches. These planners use preprocessing and query stages, and are aimed at planning many times in the same environment. In contrast, our preprocessing stage creates a representation of the configuration space that can be easily modified in real time to account for changes in the environment. As with previous approaches, we begin by constructing a graph that represents a roadmap in the configuration space, but we do not construct this graph for a specific workspace. Instead, we construct the graph for an obstacle-free workspace, and encode the mapping from workspace cells to nodes and arcs in the graph. When the environment changes, this mapping is used to make the appropriate modifications to the graph, and plans can be generated by searching the modified graph. After presenting the approach, we address a number of performance issues via extensive simulation results for robots with as many as twenty degrees of freedom. We evaluate memory requirements, preprocessing time, and the time to dynamically modify the graph and replan, all as a function of the number of degrees of freedom of the robot.
A Probabilistic Roadmap Planner for Flexible Objects with a Workspace Medial-Axis-Based Sampling Approach
, 1999
"... Probabilistic roadmap planners have been used with success to plan paths for flexible objects such as metallic plates or plastic flexible pipes. This paper improves the performance of these planners by using the medial axis of the workspace to guide the random sampling. At a preprocessing stage, the ..."
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Cited by 55 (4 self)
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Probabilistic roadmap planners have been used with success to plan paths for flexible objects such as metallic plates or plastic flexible pipes. This paper improves the performance of these planners by using the medial axis of the workspace to guide the random sampling. At a preprocessing stage, the medial axis of the workspace is computed using a recent efficient algorithm. Then the flexible object is fitted at random points along the medial axis. The energy of all generated configurations is minimized and the planner proceeds to connect them with low-energy quasi-static paths in a roadmap that captures the connectivity of the free space. Given an initial and a final configuration, the planner connects these to the roadmap and searches the roadmap for a path. Our experimental results show that the new sampling scheme is successful in identifying critical deformations of the object along solution paths which results in a significant reduction of the computation time. Our work on planning for flexible objects has applications in industrial settings, virtual reality environments, and medicine.
Soft robotics: biological inspiration, state of the art, and future research.
- Appl. Bionics Biomech.
, 2008
"... Traditional robots have rigid underlying structures that limit their ability to interact with their environment. For example, conventional robot manipulators have rigid links and can manipulate objects using only their specialised end effectors. These robots often encounter difficulties operating i ..."
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Cited by 53 (3 self)
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Traditional robots have rigid underlying structures that limit their ability to interact with their environment. For example, conventional robot manipulators have rigid links and can manipulate objects using only their specialised end effectors. These robots often encounter difficulties operating in unstructured and highly congested environments. A variety of animals and plants exhibit complex movement with soft structures devoid of rigid components. Muscular hydrostats (e.g. octopus arms and elephant trunks) are almost entirely composed of muscle and connective tissue and plant cells can change shape when pressurised by osmosis. Researchers have been inspired by biology to design and build soft robots. With a soft structure and redundant degrees of freedom, these robots can be used for delicate tasks in cluttered and/or unstructured environments. This paper discusses the novel capabilities of soft robots, describes examples from nature that provide biological inspiration, surveys the state of the art and outlines existing challenges in soft robot design, modelling, fabrication and control.
Planning Paths for Elastic Objects Under Manipulation Constraints
- International Journal of Robotics Research
, 2001
"... This paper addresses the problem of planning paths for an elastic object from an initial to a final configuration in a static environment. It is assumed that the object is manipulated by two actuators and that it does not touch the obstacles in its environment at any time. The object may need to ..."
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Cited by 51 (9 self)
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This paper addresses the problem of planning paths for an elastic object from an initial to a final configuration in a static environment. It is assumed that the object is manipulated by two actuators and that it does not touch the obstacles in its environment at any time. The object may need to deform in order to achieve a collision-free path from the initial to the final configuration. Any required deformations are automatically computed by our planner according to the principles of elasticity theory from mechanics. The problem considered in this paper differs significantly from that of planning for a rigid or an articulated object. In the first part of the paper we point out these differences and highlight the reasons that make planning for elastic objects an extremely difficult task. We then present a randomized algorithm for computing collision-free paths for elastic objects under the above-mentioned restrictions of manipulation.
The Gaussian sampling strategy for probabilistic roadmap planners
- in: IEEE International Conference on Robotics and Automation
, 1999
"... Probabilistic roadmap planners (PRMs) form a relatively new technique for motion planning that has shown great potential. A critical aspect of PRM is the probabilistic strategy used to sample the free configuration space. In this paper we present a new, sample sampling strategy, which we call the Ga ..."
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Cited by 40 (1 self)
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Probabilistic roadmap planners (PRMs) form a relatively new technique for motion planning that has shown great potential. A critical aspect of PRM is the probabilistic strategy used to sample the free configuration space. In this paper we present a new, sample sampling strategy, which we call the Gaussian sampler, that gives a much better coverage of the dificult parts of the free Configuration space. The approach uses only elementary operations which makes it suitable for many different planning problems. Experiments indicate that the technique is very eficient indeed. 1
Towards Planning for Elastic Objects
- ROBOTICS: THE ALGORITHMIC PERSPECTIVE
, 1998
"... This paper investigates the problem of path planning for a thin elastic plate. The underlying geometric model for the plate is provided by a Bezier representation. The geometric model is augmented by a realistic mechanical model. The latter permits the computation of the shape of the plate with resp ..."
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Cited by 39 (6 self)
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This paper investigates the problem of path planning for a thin elastic plate. The underlying geometric model for the plate is provided by a Bezier representation. The geometric model is augmented by a realistic mechanical model. The latter permits the computation of the shape of the plate with respect to a set of grasping constrints by minimizing the elastic energy of the deformation. We use a probabilistic roadmap planner to compute paths for the plate and we present a number of experimental results to illustrate our approach. Our work is a first step towards considering the physical properties of objects when planning.
Path planning for deformable robots in complex environments
- In Robotics: Systems and Science
, 2005
"... Abstract — We present an algorithm for path planning for a flexible robot in complex environments. Our algorithm computes a collision free path by taking into account geometric and physical constraints, including obstacle avoidance, non-penetration constraint, volume preservation, surface tension, a ..."
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Cited by 28 (3 self)
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Abstract — We present an algorithm for path planning for a flexible robot in complex environments. Our algorithm computes a collision free path by taking into account geometric and physical constraints, including obstacle avoidance, non-penetration constraint, volume preservation, surface tension, and energy minimization. We describe a new algorithm for collision detection between a deformable robot and fixed obstacles using graphics processors. We also present techniques to efficiently handle complex deformable models composed of tens of thousands of polygons and obtain significant performance improvement over previous approaches. Moreover, we demonstrate a practical application of our algorithm in performing path planning of catheters in liver chemoembolization. I.
