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Motion planning

About: Motion planning is a research topic. Over the lifetime, 32846 publications have been published within this topic receiving 553548 citations.


Papers
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Proceedings ArticleDOI
29 Oct 2001
TL;DR: A cooperative scheme for localizing the robots based on visual imagery that is more robust than decentralized localization and a set of control algorithms that allow the robots to maintain a prescribed formation are described.
Abstract: We describe a framework for coordinating multiple robots in cooperative manipulation tasks in which vision is used for establishing relative position and orientation and maintaining formation. The two key contributions are a cooperative scheme for localizing the robots based on visual imagery that is more robust than decentralized localization, and a set of control algorithms that allow the robots to maintain a prescribed formation (shape and size). The ability to maintain a prescribed formation allows the robots to "trap" objects in their midst, and to "flow" the formation to a desired position. We derive the cooperative localization and control algorithms and present experimental results that illustrate the implementation and the performance of these algorithms.

211 citations

Proceedings ArticleDOI
01 Jan 1993
TL;DR: In this article, the problem of steering a mobile robot with N trailers by converting the system into chained form, doing the path-planning in the chained form coordinates, and converting the path back into the original coordinates is solved.
Abstract: Shows how the machinery of exterior differential systems can be used to help solve nonholonomic motion planning problems. Since the Goursat normal form, for exterior differential systems is dual to chained form for vector fields, the authors solve the problem of steering a mobile robot with N trailers by converting the system into chained form, doing the path-planning in the chained form coordinates, and converting the path back into the original coordinates. Simulations of the N-trailer system parallel parking and backing into a loading dock are included. >

210 citations

Journal ArticleDOI
TL;DR: An extensive study of the most important methods for autonomous exploration and mapping of unknown environments is presented and a representative subset of these techniques has been chosen to be analysed.
Abstract: To date, a large number of algorithms to solve the problem of autonomous exploration and mapping has been presented. However, few efforts have been made to compare these techniques. In this paper, an extensive study of the most important methods for autonomous exploration and mapping of unknown environments is presented. Furthermore, a representative subset of these techniques has been chosen to be analysed. This subset contains methods that differ in the level of multi-robot coordination and in the grade of integration with the simultaneous localization and mapping (SLAM) algorithm. These exploration techniques were tested in simulation and compared using different criteria as exploration time or map quality. The results of this analysis are shown in this paper. The weaknesses and strengths of each strategy have been stated and the most appropriate algorithm for each application has been determined.

210 citations

Proceedings ArticleDOI
09 Nov 2010
TL;DR: A filter that is able to simultaneously estimate the behaviors of traffic participants and anticipate their future trajectories and achieves a comprehensive situational understanding, inevitable for autonomous vehicles and driver assistance systems is presented.
Abstract: This paper presents a filter that is able to simultaneously estimate the behaviors of traffic participants and anticipate their future trajectories. This is achieved by recognizing the type of situation derived from the local situational context, which subsumes all information relevant for the drivers decision making. By explicitly taking into account the interactions between vehicles, it achieves a comprehensive situational understanding, inevitable for autonomous vehicles and driver assistance systems. This provides the necessary information for safe behavior decision making or motion planning. The filter is modeled as a Dynamic Bayesian Network. The factored state space, modeling the causal dependencies, allows to describe the models in a compact fashion and reduces the computational complexity of the inference process. The filter is evaluated in the context of a highway scenario, showing a good performance even with very noisy measurements. The presented framework is intended to be used in traffic environments but can be easily transferred to other robotic domains.

209 citations

Journal ArticleDOI
TL;DR: In this article, the authors study three different trajectories for the mobile landmark, namely, Scan, Double Scan, and Hilbert, and show that any deterministic trajectory that covers the whole area offers significant benefits compared to a random movement of the landmark.

208 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20231,512
20223,388
20212,138
20202,668
20192,648
20182,266