Author name cluster

Paul A. Beardsley

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.

15 papers

1 author row

ICRA Conference 2019 Conference Paper

An Approach for Semantic Segmentation of Tree-like Vegetation

Sundara Tejaswi Digumarti
Lukas Schmid 0001
Giuseppe Maria Rizzi
Juan I. Nieto 0001
Roland Siegwart
Paul A. Beardsley
Cesar Cadena 0001

This paper presents a pipeline for semantic segmentation of trees into their components. Given a single RGB-D image of a tree, we employ a deep network to predict labels to classify each pixel of the tree into trunk, branches, twigs and leaves. Multiple convolutional neural network architectures to combine the complementary modalities of depth and colour data are investigated. An asynchronous training approach where two networks trained separately on RGB and depth encoded as a 3-channel HHA image are combined using a late fusion architecture with different learning rates performs the best. Training and evaluation are performed on a synthetic dataset of 6 species of broadleaf trees. We further demonstrate the network's generalization capabilities, across various tree species on the synthetic dataset, achieving an accuracy of upto 92. 5%. Furthermore, we present a qualitative evaluation of our approach on real-world data.

ICRA Conference 2019 Conference Paper

Mobile Robotic Painting of Texture

Majed El Helou
Stephan Mandt
Andreas Krause 0001
Paul A. Beardsley

Robotic painting is well-established in controlled factory environments, but there is now potential for mobile robots to do functional painting tasks around the everyday world. An obvious first target for such robots is painting a uniform single color. A step further is the painting of textured images. Texture involves a varying appearance, and requires that paint is delivered accurately onto the physical surface to produce the desired effect. Robotic painting of texture is relevant for architecture and in themed environments. A key challenge for robotic painting of texture is to take a desired image as input, and to generate the paint commands to as closely as possible create the desired appearance, according to the robotic capabilities. This paper describes a deep learning approach to take an input ink map of a desired texture, and infer robotic paint commands to produce that texture. We analyze the trade-offs between quality of reconstructed appearance and ease of execution. Our method is general for different kinds of robotic paint delivery systems, but the emphasis here is on spray painting. More generally, the framework can be viewed as an approach for solving a specific class of inverse imaging problems.

IROS Conference 2018 Conference Paper

StreetMap - Mapping and Localization on Ground Planes using a Downward Facing Camera

Xu Chen
Anurag Sai Vempati
Paul A. Beardsley

This paper describes a system to map a ground-plane, and to subsequently use the map for localization of a mobile robot. The robot has a downward-facing camera, and works on a variety of ground textures including general texture like tarmac, man-made designs like carpet, and rectilinear textures like indoor tiles or outdoor slabs. Such textures provide a basis for measuring relative motion (i. e. computer mouse functionality). But the goal here is the more challenging one of absolute localization. The paper describes a complete working pipeline to build a globally consistent map of a given ground-plane and subsequently to localize within this map at real-time. Two algorithms are described. The first is a feature-based approach which is general to any ground plane texture. The second algorithm takes advantage of the extra constraints available for common rectilinear textures like indoor tiling, paving slabs, and laid brickwork. Quantitative and qualitative experimental results are shown for mapping and localization on a variety of ground-planes.

IROS Conference 2017 Conference Paper

Handshakiness: Benchmarking for human-robot hand interactions

Espen Knoop
Moritz Bächer
Vincent Wall
Raphael Deimel
Oliver Brock
Paul A. Beardsley

Handshakes are common greetings, and humans therefore have strong priors of what a handshake should feel like. This makes it challenging to create compelling and realistic human-robot handshakes, necessitating the consideration of human haptic perception in the design of robot hands. At its most basic level, haptic perception is encoded by contact points and contact pressure distributions on the skin. This motivates our work on measuring the contact area and contact pressure in human handshaking interactions. We present two benchmarking experiments in this regard, measuring the contact locations in human-human/human-robot handshaking and the contact pressure distribution for handshakes with a sensorized palm. We present results from human studies with the benchmarking experiments, providing a baseline for comparison with robot hands as well as presenting new insights into human handshaking. We also show initial work in using these results for the evaluation of robot hands, and progressing towards iterative design of robot hands optimized for social hand interactions.

IROS Conference 2017 Conference Paper

Onboard real-time dense reconstruction of large-scale environments for UAV

Anurag Sai Vempati
Igor Gilitschenski
Juan I. Nieto 0001
Paul A. Beardsley
Roland Siegwart

In this paper, we propose a GPU parallelized SLAM system capable of using photometric and inertial data together with depth data from an active RGB-D sensor to build accurate dense 3D maps of indoor environments. We describe several extensions to existing dense SLAM techniques that allow us to operate in real-time onboard memory constrained robotic platforms. Our primary contribution is a memory management algorithm that scales to large scenes without being limited by GPU memory resources. Moreover, by integrating a visual-inertial odometry system, we robustly track the camera pose even on an agile platform such as a quadrotor UAV. Our robust camera tracking framework can deal with fast camera motions and varying environments by relying on depth, color and inertial motion cues. Global consistency is achieved via regular checking for loop closures in conjunction with a pose graph, as a basis for corrective deformation of the 3D map. Our efficient SLAM system is capable of producing highly dense meshes up to 5mm resolution at rates close to 60Hz fully onboard a UAV. Experimental validations both in simulation and on a real-world platform, show that our approach is fast, more robust and more memory efficient than state-of-the-art techniques, while obtaining better or comparable accuracy.

IROS Conference 2016 Conference Paper

Tree cavity inspection using aerial robots

Kelly Steich
Mina Kamel 0001
Paul A. Beardsley
Martin K. Obrist
Roland Siegwart
Thibault Lachat

We present an aerial robotic platform for remote tree cavity inspection, based on a hexacopter Micro-Aerial vehicle (MAV) equipped with a dexterous manipulator. The goal is to make the inspection process safer and more efficient and facilitate data collection about tree cavities, which are important for the conservation of biodiversity in forest ecosystems. This work focuses on two key enabling technologies, namely a vision-based cavity detection system and strategies for high level control of the MAV and manipulator. The results of both simulation and real-world experiments are discussed at the end of the paper and demonstrate the effectiveness of our approach.

ICRA Conference 2015 Conference Paper

Gesture based human - Multi-robot swarm interaction and its application to an interactive display

Javier Alonso-Mora
S. Haegeli Lohaus
Philipp Leemann
Roland Siegwart
Paul A. Beardsley

A taxonomy for gesture-based interaction between a human and a group (swarm) of robots is described. Methods are classified into two categories. First, free-form interaction, where the robots are unconstrained in position and motion and the user can use deictic gestures to select subsets of robots and assign target goals and trajectories. Second, shape-constrained interaction, where the robots are in a configuration shape that can be modified by the user. In the later, the user controls a subset of meaningful degrees of freedom defining the overall shape instead of each robot directly. A multi-robot interactive display is described where a depth sensor is used to recognize human gesture, determining the commands sent to a group comprising tens of robots. Experimental results with a preliminary user study show the usability of the system.

ICRA Conference 2014 Conference Paper

Shared control of autonomous vehicles based on velocity space optimization

Javier Alonso-Mora
Pascal Gohl
Scott Watson
Roland Siegwart
Paul A. Beardsley

This paper presents a method for shared control of a vehicle. The driver commands a preferred velocity which is transformed into a collision-free local motion that respects the actuator constraints and allows for smooth and safe control. Collision-free local motions are achieved with an extension of velocity obstacles that takes into account dynamic constraints and a grid-based map representation. To limit the freedom of the driver, a global guidance trajectory can be included, which specifies the areas where the vehicle is allowed to drive in each time instance. The low computational complexity of the method makes it well suited for multi-agent settings and high update rates and both a centralized and a distributed algorithm are provided that allow for real-time control of tens of vehicles. Extensive experimental results with real robotic wheelchairs at relatively high speeds in tight scenarios are presented.

IROS Conference 2014 Conference Paper

Spatio-temporal laser to visual/inertial calibration with applications to hand-held, large scale scanning

Joern Rehder
Paul A. Beardsley
Roland Siegwart
Paul Timothy Furgale

This work presents a novel approach to spatio-temporal calibration of a laser range finder (LRF) with respect to a combination of a stereo camera and an inertial measurement unit (IMU). Spatial calibration between an LRF and a camera has been extensively studied, but so far the temporal relationship between the two has largely been neglected. While this may be sufficient for applications where the setup is mounted on a vehicle, which imposes bounds on the dynamics, we aim for employment on a hand-held scanning device, where angular velocities can easily exceed hundreds of degrees per second. Employing a continuous-time batch estimation framework, this work demonstrates that the transformation between the LRF and the visual/inertial setup-but also its temporal relationship-can be estimated accurately. In contrast to the majority of established calibration approaches, our approach does not require an overlap in the field of view of the LRF and camera, allowing for previously infeasible sensor configurations to be calibrated. Preliminary results for a novel hand-held scanning device suggest improvements in 3D reconstructions and image based point cloud coloring, especially for highly dynamic motions.

ICRA Conference 2014 Conference Paper

Viewpoint and trajectory optimization for animation display with aerial vehicles

Marcel Schoch
Javier Alonso-Mora
Roland Siegwart
Paul A. Beardsley

This paper presents a method to optimize the position and trajectory of each aerial vehicle within a large group that displays objects and animations in 3D space. The input is a single object or an animation created by an artist. In a first step, goal positions for the given number of vehicles and representing the object are optimized with respect to a known viewpoint. For displaying an animation, an optimal trajectory satisfying the dynamic constraints of each vehicle is computed using B-splines. Finally, a trajectory following controller is described, which provides the preferred velocity, later optimized to be collision-free with respect to all neighboring vehicles.

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.

IROS Conference 2013 Conference Paper

Design and control of a spherical omnidirectional blimp

Michael Burri
Laura Gasser
M. Käch
Matthias Krebs
S. Laube
Anton Ledergerber
Daniel Meier
R. Michaud

This paper presents Skye, a novel blimp design. Skye is a helium-filled sphere of diameter 2. 7m with a strong inelastic outer hull and an impermeable elastic inner hull. Four tetrahedrally-arranged actuation units (AU) are mounted on the hull for locomotion, with each AU having a thruster which can be rotated around a radial axis through the sphere center. This design provides redundant control in the six degrees of freedom of motion, and Skye is able to move omnidirectionally and to rotate around any axis. A multi-camera module is also mounted on the hull for capture of aerial imagery or live video stream according to an ‘eyeball’ concept — the camera module is not itself actuated, but the whole blimp is rotated in order to obtain a desired camera view. Skye is safe for use near people — the double hull minimizes the likelihood of rupture on an unwanted collision; the propellers are covered by grills to prevent accidental contact; and the blimp is near neutral buoyancy so that it makes only a light impact on contact and can be readily nudged away. The system is portable and deployable by a single operator — the electronics, AUs, and camera unit are mounted externally and are detachable from the hull during transport; operator control is via an intuitive touchpad interface. The motivating application is in entertainment robotics. Skye has a varied motion vocabulary such as swooping and bobbing, plus internal LEDs for visual effect. Computer vision enables interaction with an audience. Experimental results show dexterous maneuvers in indoor and outdoor environments, and non-dangerous impacts between the blimp and humans.

IROS Conference 2012 Conference Paper

Object and animation display with multiple aerial vehicles

Javier Alonso-Mora
Marcel Schoch
Andreas Breitenmoser
Roland Siegwart
Paul A. Beardsley

This paper presents a fully automated method to display objects and animations in 3D with a group of aerial vehicles. The system input is a single object or an animation (sequence of objects) created by an artist. The first stage is to generate physical goal configurations and robot colors to represent the objects with the available number of robots. The run-time system includes algorithms for goal assignment, path planning and local reciprocal collision avoidance that guarantee smooth, fast and oscillation-free motion. The presented algorithms are tested in simulations and verified with real quadrotor helicopters and scale to large robot swarms.

ICRA Conference 2012 Conference Paper

Reciprocal collision avoidance for multiple car-like robots

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

In this paper a method for distributed reciprocal collision avoidance among multiple non-holonomic robots with bike kinematics is presented. The proposed algorithm, bicycle reciprocal collision avoidance (B-ORCA), builds on the concept of optimal reciprocal collision avoidance (ORCA) for holonomic robots but furthermore guarantees collision-free motions under the kinematic constraints of car-like vehicles. The underlying principle of the B-ORCA algorithm applies more generally to other kinematic models, as it combines velocity obstacles with generic tracking control. The theoretical results on collision avoidance are validated by several simulation experiments between multiple car-like robots.

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.