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Motion planning in urban environments

Journal of Field Robotics, 2008
AbstractWe present the motion planning framework for an autonomous vehicle navigating through urban environments. Such environments present a number of motion planning challenges, including ultrareliability, high‐speed operation, complex intervehicle interaction, parking in large unstructured lots, and constrained maneuvers.
Dave Ferguson 0001   +2 more
openaire   +1 more source

Self-indexed Motion Planning

Information Systems, 2017
Motion planning is a central problem for robotics. The PRM algorithm is, together with the asymptotically optimal variant PRM*, the standard method to maintain a (collision-free) roadmap in the configuration space. The PRM algorithm is randomized, and requires a large number of high-dimensional point samples generated online, hence a sub-problem to ...
Angello Hoyos   +3 more
openaire   +1 more source

Motion planning of a UAV using a kinodynamic motion planning method

IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society, 2013
In this research, we extend the kinodynamic motion planning using “nonlinear anisotropic damping forces (NADFs),” which had been applied to a point mass in the previous research, to the motion planning of “unmanned arerial vehicles (UAVs)”. In the proposed system, we realize the autonomous locomotion for AUVs by combining the nonholonomic control ...
Kimiko Motonaka   +2 more
openaire   +1 more source

Motion Planning: Recent Developments

2006
A key trait of an autonomous robot is the ability to plan its own motion in order to accomplish specified tasks. Often, the objective of motion planning is to change the state of the world by computing a sequence of admissible motions for the robot.
H√©ctor Gonz√°lez-Ba√±os   +2 more
openaire   +1 more source

Speed Planning for a Maneuvering Motion

Journal of Intelligent and Robotic Systems, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kao-Shing Hwang, Ming-Yi Ju
openaire   +1 more source

Integrated Grasp and motion planning

2010 IEEE International Conference on Robotics and Automation, 2010
In this work, we present an integrated planner for collision-free single and dual arm grasping motions. The proposed Grasp-RRT planner combines the three main tasks needed for grasping an object: finding a feasible grasp, solving the inverse kinematics and searching a collision-free trajectory that brings the hand to the grasping pose.
Nikolaus Vahrenkamp   +3 more
openaire   +1 more source

Motion planning in stereotaxic radiosurgery

[1993] Proceedings IEEE International Conference on Robotics and Automation, 1993
Stereotaxic radiosurgery is a procedure that uses a beam of radiation as an ablative surgical instrument to destroy brain tumors (or more generally, brain lesions). The beam is produced by a linear accelerator that is moved by a mechanical gantry. Radiation is concentrated by crossfiring at the tumor from multiple directions, to reduce the amount of ...
Achim Schweikard   +2 more
openaire   +1 more source

Topology in Motion Planning

2005
Many motion planning, artificial intelligence, and mobile robot planning techniques exploit topology, as encoded in the free space, to aid in generating concise maps and efficient planners. Prior work of the authors has used the generalized Voronoi diagram, which is a topological map that has a natural embedding into the free space.
Howie Choset, Alfred A. Rizzi
openaire   +1 more source

Adaptive Motion Planning

2018
Mobile robots are increasingly being deployed in the real world in response to a heightened demand for applications such as transportation, delivery and inspection. The motion planning systems for these robots are expected to have consistent performance across the wide range of scenarios that they encounter.
openaire   +1 more source

Planning compliant motion strategies

Proceedings IEEE International Symposium on Intelligent Control 1988, 1989
This paper describes a planning program that synthesizes compliant motion strategies, in which an object in the grasp of a robot slides along obstacles, in an attempt to reach a goal region. The input to the planner is a model of the task geometry, a start region, and a goal region. To make the planning problem tractable, we reduce the task geometry to
openaire   +1 more source

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