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Martin Rufli

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

5 papers

1 author row

ICRA Conference 2013 Conference Paper

Collision avoidance for multiple agents with joint utility maximization

Javier Alonso-Mora
Martin Rufli
Roland Siegwart
Paul A. Beardsley

In this paper a centralized method for collision avoidance among multiple agents is presented. It builds on the velocity obstacle (VO) concept and its extensions to arbitrary kino-dynamics and is applicable to heterogeneous groups of agents (with respect to size, kino-dynamics and aggressiveness) moving in 2D and 3D spaces. In addition, both static and dynamic obstacles can be considered in the framework. The method maximizes a joint utility function and is formulated as a mixed-integer quadratic program, where online computation can be achieved as a trade-off with solution optimality. In experiments with groups of two to 50 agents the benefits of the joint utility optimization are shown. By construction, it's suboptimal variant is at least as good as comparable decentralized methods, while retaining online capability for small groups of agents. In its optimal variant, the proposed algorithm can provide a benchmark for distributed collision avoidance methods, in particular for those based on the VO concept that take interaction into account.

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ICRA Conference 2011 Conference Paper

Multi-robot system for artistic pattern formation

Javier Alonso-Mora
Andreas Breitenmoser
Martin Rufli
Roland Siegwart
Paul A. Beardsley

This paper describes work on multi-robot pattern formation. Arbitrary target patterns are represented with an optimal robot deployment, using a method that is independent of the number of robots. Furthermore, the trajectories are visually appealing in the sense of being smooth, oscillation free, and showing fast convergence. A distributed controller guarantees collision free trajectories while taking into account the kinematics of differentially driven robots. Experimental results are provided for a representative set of patterns, for a swarm of up to ten physical robots, and for fifty virtual robots in simulation.

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ICRA Conference 2010 Conference Paper

On the design of deformable input- / state-lattice graphs

Martin Rufli
Roland Siegwart

In this paper we describe a novel and simple to implement yet effective lattice design algorithm, which simultaneously produces input and state-space sampled lattice graphs. The presented method is an extension to the ideas suggested by Bicchi et al. on input lattices and is applicable to systems which can be brought into (2, n) chained form, such as kinematic models of unicycles, bicycles, differential-drive robots and car-like vehicles (pulling several trailers). We further show that a transformation from chained form to path coordinates allows the resulting lattice to be bent along any C 1 continuous path. We exploit this fact by shaping it along the skeleton of arbitrary structured environments, such as the center of road lanes and corridors. In our experiments in both structured (i. e. on-road) and unstructured (i. e. parking lot) scenarios, we successfully demonstrate for the first time the applicability of lattice-based planning approaches to search queries in arbitrary environments.

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ICRA Conference 2009 Conference Paper

Smooth path planning in constrained environments

Martin Rufli
Dave Ferguson 0001
Roland Siegwart

In this paper we describe a novel path planning approach for mobile robots operating in indoor environments. In such scenarios, robots must be able to maneuver in crowded spaces, partially filled with static and dynamic obstacles (such as people). Our approach produces smooth, complex maneuvers over large distances through the use of an anytime graph search algorithm applied to a novel multi-resolution state lattice, where the resolution is adapted based on both environmental characteristics and task characteristics. In addition, we present a novel approach for generating fast globally optimal trajectories in constrained spaces (i. e. rooms connected via doors and hallways). This approach exploits offline precomputation to provide extremely efficient online performance and is applicable to a wide range of both indoor and outdoor navigation scenarios. By combining an anytime, multi-resolution lattice-based search algorithm with our precomputation technique, globally optimal trajectories in up to four dimensions (2D position, heading and velocity) are obtained in real-time.

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IROS Conference 2008 Conference Paper

Automatic detection of checkerboards on blurred and distorted images

Martin Rufli
Davide Scaramuzza 0001
Roland Siegwart

Most of the existing camera calibration toolboxes require the observation of a checkerboard shown by the user at different positions and orientations. This paper presents an algorithm for the automatic detection of checkerboards, described by the position and the arrangement of their corners, in blurred and heavily distorted images. The method can be applied to both perspective and omnidirectional cameras. An existing corner detection method is evaluated and its strengths and shortcomings in detecting corners on blurred and distorted test image sets are analyzed. Starting from the results of this analysis, several improvements are proposed, implemented, and tested. We show that the proposed algorithm is able to consistently identify 80% of the corners on omnidirectional images of as low as VGA resolution and approaches 100% correct corner extraction at higher resolutions, outperforming the existing implementation significantly. The performance of the proposed method is demonstrated on several test image sets of various resolution, distortion, and blur, which are exemplary for different kinds of camera-mirror setups in use.

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