2,653 research outputs found
Coupled path and motion planning for a rover-manipulator system
This paper introduces a motion planning strategy aimed
at the coordination of a rover and manipulator. The main
purpose is to fetch samples of scientific interest that could
be placed on difficult locations, requiring to maximize
the workspace of the combined system. In order to validate
this strategy, a simulation environment has been built, based on the VORTEX Studio platform. A virtual model of the ExoTer rover prototype, owned by the European Space Agency, has been used together with the same robot control software. Finally, we show in this paper the benefits of validating the proposed strategy on simulation, prior to its future use on the real experimental rover.Universidad de Málaga. Campus de Excelencia Internacional AndalucĂa Tec
Admissible Velocity Propagation : Beyond Quasi-Static Path Planning for High-Dimensional Robots
Path-velocity decomposition is an intuitive yet powerful approach to address
the complexity of kinodynamic motion planning. The difficult trajectory
planning problem is solved in two separate, simpler, steps: first, find a path
in the configuration space that satisfies the geometric constraints (path
planning), and second, find a time-parameterization of that path satisfying the
kinodynamic constraints. A fundamental requirement is that the path found in
the first step should be time-parameterizable. Most existing works fulfill this
requirement by enforcing quasi-static constraints in the path planning step,
resulting in an important loss in completeness. We propose a method that
enables path-velocity decomposition to discover truly dynamic motions, i.e.
motions that are not quasi-statically executable. At the heart of the proposed
method is a new algorithm -- Admissible Velocity Propagation -- which, given a
path and an interval of reachable velocities at the beginning of that path,
computes exactly and efficiently the interval of all the velocities the system
can reach after traversing the path while respecting the system kinodynamic
constraints. Combining this algorithm with usual sampling-based planners then
gives rise to a family of new trajectory planners that can appropriately handle
kinodynamic constraints while retaining the advantages associated with
path-velocity decomposition. We demonstrate the efficiency of the proposed
method on some difficult kinodynamic planning problems, where, in particular,
quasi-static methods are guaranteed to fail.Comment: 43 pages, 14 figure
WGIT*: Workspace-Guided Informed Tree for Motion Planning in Restricted Environments
The motion planning of robots faces formidable challenges in restricted environments, particularly in the aspects of rapidly searching feasible solutions and converging towards optimal solutions. This paper proposes Workspace-guided Informed Tree (WGIT*) to improve planning efficiency and ensure high-quality solutions in restricted environments. Specifically, WGIT* preprocesses the workspace by constructing a hierarchical structure to obtain critical restricted regions and connectivity information sequentially. The refined workspace information guides the sampling and exploration of WGIT*, increasing the sample density in restricted areas and prioritizing the search tree exploration in promising directions, respectively. Furthermore, WGIT* utilizes gradually enriched configuration space information as feedback to rectify the guidance from the workspace and balance the information of the two spaces, which leads to efficient convergence toward the optimal solution. The theoretical analysis highlights the valuable properties of the proposed WGIT*. Finally, a series of simulations and experiments verify the ability of WGIT* to quickly find initial solutions and converge towards optimal solutions
- …