4,377 research outputs found
Coordinated Robot Navigation via Hierarchical Clustering
We introduce the use of hierarchical clustering for relaxed, deterministic
coordination and control of multiple robots. Traditionally an unsupervised
learning method, hierarchical clustering offers a formalism for identifying and
representing spatially cohesive and segregated robot groups at different
resolutions by relating the continuous space of configurations to the
combinatorial space of trees. We formalize and exploit this relation,
developing computationally effective reactive algorithms for navigating through
the combinatorial space in concert with geometric realizations for a particular
choice of hierarchical clustering method. These constructions yield
computationally effective vector field planners for both hierarchically
invariant as well as transitional navigation in the configuration space. We
apply these methods to the centralized coordination and control of
perfectly sensed and actuated Euclidean spheres in a -dimensional ambient
space (for arbitrary and ). Given a desired configuration supporting a
desired hierarchy, we construct a hybrid controller which is quadratic in
and algebraic in and prove that its execution brings all but a measure zero
set of initial configurations to the desired goal with the guarantee of no
collisions along the way.Comment: 29 pages, 13 figures, 8 tables, extended version of a paper in
preparation for submission to a journa
Human Motion Trajectory Prediction: A Survey
With growing numbers of intelligent autonomous systems in human environments,
the ability of such systems to perceive, understand and anticipate human
behavior becomes increasingly important. Specifically, predicting future
positions of dynamic agents and planning considering such predictions are key
tasks for self-driving vehicles, service robots and advanced surveillance
systems. This paper provides a survey of human motion trajectory prediction. We
review, analyze and structure a large selection of work from different
communities and propose a taxonomy that categorizes existing methods based on
the motion modeling approach and level of contextual information used. We
provide an overview of the existing datasets and performance metrics. We
discuss limitations of the state of the art and outline directions for further
research.Comment: Submitted to the International Journal of Robotics Research (IJRR),
37 page
Clustering-Based Robot Navigation and Control
In robotics, it is essential to model and understand the topologies of configuration spaces in order to design provably correct motion planners. The common practice in motion planning for modelling configuration spaces requires either a global, explicit representation of a configuration space in terms of standard geometric and topological models, or an asymptotically dense collection of sample configurations connected by simple paths, capturing the connectivity of the underlying space. This dissertation introduces the use of clustering for closing the gap between these two complementary approaches. Traditionally an unsupervised learning method, clustering offers automated tools to discover hidden intrinsic structures in generally complex-shaped and high-dimensional configuration spaces of robotic systems. We demonstrate some potential applications of such clustering tools to the problem of feedback motion planning and control.
The first part of the dissertation presents the use of hierarchical clustering for relaxed, deterministic coordination and control of multiple robots. We reinterpret this classical method for unsupervised learning as an abstract formalism for identifying and representing spatially cohesive and segregated robot groups at different resolutions, by relating the continuous space of configurations to the combinatorial space of trees. Based on this new abstraction and a careful topological characterization of the associated hierarchical structure, a provably correct, computationally efficient hierarchical navigation framework is proposed for collision-free coordinated motion design towards a designated multirobot configuration via a sequence of hierarchy-preserving local controllers.
The second part of the dissertation introduces a new, robot-centric application of Voronoi diagrams to identify a collision-free neighborhood of a robot configuration that captures the local geometric structure of a configuration space around the robot’s instantaneous position. Based on robot-centric Voronoi diagrams, a provably correct, collision-free coverage and congestion control algorithm is proposed for distributed mobile sensing applications of heterogeneous disk-shaped robots; and a sensor-based reactive navigation algorithm is proposed for exact navigation of a disk-shaped robot in forest-like cluttered environments.
These results strongly suggest that clustering is, indeed, an effective approach for automatically extracting intrinsic structures in configuration spaces and that it might play a key role in the design of computationally efficient, provably correct motion planners in complex, high-dimensional configuration spaces
Building Fuzzy Elevation Maps from a Ground-based 3D Laser Scan for Outdoor Mobile Robots
Mandow, A; Cantador, T.J.; Reina, A.J.; MartĂnez, J.L.; Morales, J.; GarcĂa-Cerezo, A. "Building Fuzzy Elevation Maps from a Ground-based 3D Laser Scan for Outdoor Mobile Robots," Robot2015: Second Iberian Robotics Conference, Advances in Robotics, (2016) Advances in Intelligent Systems and Computing, vol. 418. This is a self-archiving copy of the author’s accepted manuscript. The final publication is available at Springer via
http://link.springer.com/book/10.1007/978-3-319-27149-1.The paper addresses terrain modeling for mobile robots with fuzzy elevation maps by improving computational
speed and performance over previous work on fuzzy terrain identification from a three-dimensional (3D) scan. To this end,
spherical sub-sampling of the raw scan is proposed to select training data that does not filter out salient obstacles. Besides,
rule structure is systematically defined by considering triangular sets with an unevenly distributed standard fuzzy partition
and zero order Sugeno-type consequents. This structure, which favors a faster training time and reduces the number of rule
parameters, also serves to compute a fuzzy reliability mask for the continuous fuzzy surface. The paper offers a case study
using a Hokuyo-based 3D rangefinder to model terrain with and without outstanding obstacles. Performance regarding error
and model size is compared favorably with respect to a solution that uses quadric-based surface simplification (QSlim).This work was partially supported by the Spanish CICYT project DPI 2011-22443, the Andalusian project PE-2010 TEP-6101, and Universidad de Málaga-AndalucĂa Tech
Emerging robot swarm traffic
We discuss traffic patterns generated by swarms of robots while commuting to and from a base station. The overall question is whether to explicitly organise the traffic or whether a certain regularity develops `naturally'.
Human driven motorized traffic is rigidly structured in two lanes. However, army ants develop a three-lane pattern in their traffic, while human pedestrians generate a main trail and secondary trials in either direction.
Our robot swarm approach is bottom-up: designing individual agents we first investigate the mathematics of cases occurring when applying the artificial potential field method to three 'perfect' robots. We show that traffic lane pattern will not be disturbed by the internal system of forces. Next, we define models of sensor designs to account for the practical fact that robots (and ants) have limited visibility and compare the sensor models in groups of three robots. In the final step we define layouts of a highway: an unbounded open space, a trail with surpassable edges and a hard defined (walled) highway.
Having defined the preliminaries we run swarm simulations and look for emerging traffic patterns. Apparently, depending on the initial situation a variety of lane patterns occurs, however, high traffic densities do delay the emergence of traffic lanes considerably. Overall we conclude that regularities do emerge naturally and can be turned into an advantage to obtain efficient robot traffic
- …