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106
RapidlyExploring Random Trees: Progress and Prospects
 Algorithmic and Computational Robotics: New Directions
, 2000
"... this paper, which presents randomized, algorithmic techniques for path planning that are particular suited for problems that involve dierential constraints. ..."
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Cited by 228 (25 self)
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this paper, which presents randomized, algorithmic techniques for path planning that are particular suited for problems that involve dierential constraints.
Randomized Kinodynamic Motion Planning with Moving Obstacles
, 2000
"... We present a randomized motion planner for robots that must avoid moving obstacles and achieve a specified goal under kinematic and dynamic constraints. The planner samples the robot's statetime space by picking control inputs at random and integrating the equations of motion. The result is a roa ..."
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Cited by 190 (12 self)
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We present a randomized motion planner for robots that must avoid moving obstacles and achieve a specified goal under kinematic and dynamic constraints. The planner samples the robot's statetime space by picking control inputs at random and integrating the equations of motion. The result is a roadmap of sampled statetime points, called milestones, connected by short admissible trajectories. The planner does not precompute the roadmap as traditional probabilistic roadmap planners do; instead, for each planning query, it generates a new roadmap to find a trajectory between an initial and a goal statetime point. We prove in this paper that the probability that the planner fails to find such a trajectory when one exists quickly goes to 0, as the number of milestones grows. The planner has been implemented and tested successfully in both simulated and real environments. In the latter case, a vision module estimates obstacle motions just before planning starts; the planner is then allocated a small, fixed amount of time to compute a trajectory. If a change in the obstacle motion is detected while the robot executes the planned trajectory, the planner recomputes a trajectory on the fly. 1
Flatness and defect of nonlinear systems: Introductory theory and examples
 International Journal of Control
, 1995
"... We introduce flat systems, which are equivalent to linear ones via a special type of feedback called endogenous. Their physical properties are subsumed by a linearizing output and they might be regarded as providing another nonlinear extension of Kalman’s controllability. The distance to flatness is ..."
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Cited by 176 (14 self)
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We introduce flat systems, which are equivalent to linear ones via a special type of feedback called endogenous. Their physical properties are subsumed by a linearizing output and they might be regarded as providing another nonlinear extension of Kalman’s controllability. The distance to flatness is measured by a nonnegative integer, the defect. We utilize differential algebra which suits well to the fact that, in accordance with Willems ’ standpoint, flatness and defect are best defined without distinguishing between input, state, output and other variables. Many realistic classes of examples are flat. We treat two popular ones: the crane and the car with n trailers, the motion planning of which is obtained via elementary properties of planar curves. The three nonflat examples, the simple, double and variable length pendulums, are borrowed from nonlinear physics. A high frequency control strategy is proposed such that the averaged systems become flat. ∗This work was partially supported by the G.R. “Automatique ” of the CNRS and by the D.R.E.D. of the “Ministère de l’Éducation Nationale”. 1 1
Geometric Shortest Paths and Network Optimization
 Handbook of Computational Geometry
, 1998
"... Introduction A natural and wellstudied problem in algorithmic graph theory and network optimization is that of computing a "shortest path" between two nodes, s and t, in a graph whose edges have "weights" associated with them, and we consider the "length" of a path to be the sum of the weights of t ..."
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Cited by 147 (12 self)
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Introduction A natural and wellstudied problem in algorithmic graph theory and network optimization is that of computing a "shortest path" between two nodes, s and t, in a graph whose edges have "weights" associated with them, and we consider the "length" of a path to be the sum of the weights of the edges that comprise it. Efficient algorithms are well known for this problem, as briefly summarized below. The shortest path problem takes on a new dimension when considered in a geometric domain. In contrast to graphs, where the encoding of edges is explicit, a geometric instance of a shortest path problem is usually specified by giving geometric objects that implicitly encode the graph and its edge weights. Our goal in devising efficient geometric algorithms is generally to avoid explicit construction of the entire underlying graph, since the full induced graph may be very large (even exponential in the input size, or infinite). Computing an optimal
An Architecture for Autonomy
 INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
, 1998
"... An autonomous robot o ers a challenging and ideal field for the study of intelligent architectures. Autonomy within a rational behavior could be evaluated by the robot's effectiveness and robustness in carrying out tasks in different and illknown environments. It raises major requirements on the co ..."
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Cited by 133 (29 self)
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An autonomous robot o ers a challenging and ideal field for the study of intelligent architectures. Autonomy within a rational behavior could be evaluated by the robot's effectiveness and robustness in carrying out tasks in different and illknown environments. It raises major requirements on the control architecture. Furthermore, a robot as a programmable machine brings up other architectural needs, such asthe ease and quality of its specification and programming. This paper describes an integrated architecture allowing a mobile robot to plan its tasks, taking into account temporal and domain constraints, to perform corresponding actions and to control their execution in realtime, while being reactive to possible events. The general architecture is composed of three levels: a decision level, an execution level and a functional level. The later is composed of modules that embed the functions achieving sensor data processing and e ector control. The decision level is goal and eventdriven, it may have several layers, according to the application; their basic structure is a planner/supervisor pair that enables to integrate deliberation and reaction. The proposed architecture relies naturally on several representations, programming paradigms and processing approaches meeting the precise requirements specified for each level. We developed proper tools to meet these specifications and implement each level of the architecture: IxTeT a temporal planner, prs a procedural system for task refinement and supervision, Kheops for the reactive control of the functional level, and G en oM for the specification and integration of modules at that level. Validation of temporal and logical properties of the reactive parts of the system, through these tools, are presented. Instances of the proposed architecture have been already integrated into several indoor and outdoor robots. Examples from real world experimentations are provided and analyzed.
Guidelines in nonholonomic motion planning for mobile robots
 ROBOT MOTION PLANNNING AND CONTROL
, 1998
"... ..."
Trajectory Generation for the NTrailer Problem Using Goursat Normal Form
, 1995
"... In this paper, we develop the machinery of exterior differenllai forms, more particularly the Gourset normal form for a Ffaffian system, tor solving nonsoloMwic motion phdng probkms, &.e., motion planning for systems with lloniatcgrable velocity constraints. We use tbis technique to solve the probl ..."
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Cited by 58 (9 self)
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In this paper, we develop the machinery of exterior differenllai forms, more particularly the Gourset normal form for a Ffaffian system, tor solving nonsoloMwic motion phdng probkms, &.e., motion planning for systems with lloniatcgrable velocity constraints. We use tbis technique to solve the problem of rbxing a mobile robot WMI R trailers. We present an algorithm for finding a family of ~WIS~~~OM whicb will convert the system of rolling constraints on the wheels of the robot with n traiten into the GoaFapt canonical form..nRo of these transformations are studied in detail. The Gomt normal form for exterior diffemtial systems is dual to the socalled chainedform for vector fields that bas been studied previously. Consequently, we are able to give the state feedback law aad change o € e00rdinaW tovert the Ntrai4r system id0 chained form. Tllree metbods for for chainedform systems using shrosoidg and polynomiPls aa inputs are presented. The motion prpnnhag strategy Is therefore to the Ntrailer system into Gonrsat form, use this to lind the cboinedform coordinates, plan a path for the corresponding cimkdform system, and then transform the resalting traje.ctory back into the original coordinates. Simulations and h.ames of mode animations of the Ntnder system for parallel parking and backing into a loading dock using this strategy are included.
The Geometric Mechanics of Undulatory Robotic Locomotion
 INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
, 1996
"... This paper uses geometric methods to study basic problems in the mechanics and control of locomotion. We consider in detail the case of "undulatory locomotion," in which net motion is generated by coupling internal shape changes with external nonholonomic constraints. Such locomotion problems have ..."
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Cited by 56 (15 self)
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This paper uses geometric methods to study basic problems in the mechanics and control of locomotion. We consider in detail the case of "undulatory locomotion," in which net motion is generated by coupling internal shape changes with external nonholonomic constraints. Such locomotion problems have a natural geometric interpretation as a connection on a principal fiber bundle. The properties of connections lead to simplified results for studying both dynamics and issues of controllability for locomotion systems. We demonstrate the utility of this approach using a novel "Snakeboard" and a multisegmented serpentine robot which is modeled after Hirose's Active Cord Mechanism.
Path Coordination for Multiple Mobile Robots: a resolution complete algorithm
"... This paper presents a geometric based approach for multiple mobile robot motion coordination 1 . All the robot paths being computed independently, we address the problem of coordinating the motion of the robots along their path in such a way they do not collide each other. The proposed algorithm i ..."
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Cited by 49 (0 self)
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This paper presents a geometric based approach for multiple mobile robot motion coordination 1 . All the robot paths being computed independently, we address the problem of coordinating the motion of the robots along their path in such a way they do not collide each other. The proposed algorithm is based on a bounding box representation of the obstacles in the socalled coordination diagram. The algorithm is resolutioncomplete but it is shown to be complete for a large class of inputs. Despite the exponential dependency of the coordination problem, the algorithm solves efficiently problems involving up to ten robots in worst case situations, and more than 100 robots in practical ones.
MultiLevel Path Planning for Nonholonomic Robots using SemiHolonomic Subsystems
 Int. J. Robot. Res
, 1996
"... We present a new and complete multilevel approach for solving path planning problems for nonholonomic robots. At the first level a path is found that disrespects (some of) the nonholonomic constraints. At each next level a new path is generated, by transformation of the path generated at the pre ..."
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Cited by 47 (7 self)
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We present a new and complete multilevel approach for solving path planning problems for nonholonomic robots. At the first level a path is found that disrespects (some of) the nonholonomic constraints. At each next level a new path is generated, by transformation of the path generated at the previous level. The transformation is such that more nonholonomic constraints are respected than at the previous level. At the final level all nonholonomic constraints are respected. We present two techniques for these transformations. The first, which we call the Pick and Link technique, repeatedly picks pieces from the given path, and tries to replace these by more feasible ones. The second technique restricts the free configuration space to a "tube" around the given path, and a roadmap, capturing the free space connectivity within this tube, is constructed by the Probabilistic Path Planner. From this roadmap we retrieve a new, more feasible, path. In the intermediate levels we plan ...