2,437 research outputs found
MOMA: Visual Mobile Marker Odometry
In this paper, we present a cooperative odometry scheme based on the
detection of mobile markers in line with the idea of cooperative positioning
for multiple robots [1]. To this end, we introduce a simple optimization scheme
that realizes visual mobile marker odometry via accurate fixed marker-based
camera positioning and analyse the characteristics of errors inherent to the
method compared to classical fixed marker-based navigation and visual odometry.
In addition, we provide a specific UAV-UGV configuration that allows for
continuous movements of the UAV without doing stops and a minimal
caterpillar-like configuration that works with one UGV alone. Finally, we
present a real-world implementation and evaluation for the proposed UAV-UGV
configuration
A Factor Graph Approach to Multi-Camera Extrinsic Calibration on Legged Robots
Legged robots are becoming popular not only in research, but also in
industry, where they can demonstrate their superiority over wheeled machines in
a variety of applications. Either when acting as mobile manipulators or just as
all-terrain ground vehicles, these machines need to precisely track the desired
base and end-effector trajectories, perform Simultaneous Localization and
Mapping (SLAM), and move in challenging environments, all while keeping
balance. A crucial aspect for these tasks is that all onboard sensors must be
properly calibrated and synchronized to provide consistent signals for all the
software modules they feed. In this paper, we focus on the problem of
calibrating the relative pose between a set of cameras and the base link of a
quadruped robot. This pose is fundamental to successfully perform sensor
fusion, state estimation, mapping, and any other task requiring visual
feedback. To solve this problem, we propose an approach based on factor graphs
that jointly optimizes the mutual position of the cameras and the robot base
using kinematics and fiducial markers. We also quantitatively compare its
performance with other state-of-the-art methods on the hydraulic quadruped
robot HyQ. The proposed approach is simple, modular, and independent from
external devices other than the fiducial marker.Comment: To appear on "The Third IEEE International Conference on Robotic
Computing (IEEE IRC 2019)
Information-Theoretic Active Perception for Multi-Robot Teams
Multi-robot teams that intelligently gather information have the potential to transform industries as diverse as agriculture, space exploration, mining, environmental monitoring, search and rescue, and construction. Despite large amounts of research effort on active perception problems, there still remain significant challenges. In this thesis, we present a variety of information-theoretic control policies that enable teams of robots to efficiently estimate different quantities of interest. Although these policies are intractable in general, we develop a series of approximations that make them suitable for real time use.
We begin by presenting a unified estimation and control scheme based on Shannon\u27s mutual information that lets small teams of robots equipped with range-only sensors track a single static target. By creating approximate representations, we substantially reduce the complexity of this approach, letting the team track a mobile target. We then scale this approach to larger teams that need to localize a large and unknown number of targets.
We also examine information-theoretic control policies to autonomously construct 3D maps with ground and aerial robots. By using Cauchy-Schwarz quadratic mutual information, we show substantial computational improvements over similar information-theoretic measures. To map environments faster, we adopt a hierarchical planning approach which incorporates trajectory optimization so that robots can quickly determine feasible and locally optimal trajectories. Finally, we present a high-level planning algorithm that enables heterogeneous robots to cooperatively construct maps
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
An Approach for Multi-Robot Opportunistic Coexistence in Shared Space
This thesis considers a situation in which multiple robots operate in the
same environment towards the achievement of different tasks. In this situation,
please consider that not only the tasks, but also the robots themselves
are likely be heterogeneous, i.e., different from each other in their
morphology, dynamics, sensors, capabilities, etc. As an example, think
about a "smart hotel": small wheeled robots are likely to be devoted to
cleaning floors, whereas a humanoid robot may be devoted to social interaction,
e.g., welcoming guests and providing relevant information to
them upon request.
Under these conditions, robots are required not only to co-exist, but also
to coordinate their activity if we want them to exhibit a coherent and
effective behavior: this may range from mutual avoidance to avoid collisions,
to a more explicit coordinated behavior, e.g., task assignment or
cooperative localization.
The issues above have been deeply investigated in the Literature. Among
the topics that may play a crucial role to design a successful system, this
thesis focuses on the following ones:
(i) An integrated approach for path following and obstacle avoidance is
applied to unicycle type robots, by extending an existing algorithm [1]
initially developed for the single robot case to the multi-robot domain.
The approach is based on the definition of the path to be followed as a
curve f (x;y) in space, while obstacles are modeled as Gaussian functions
that modify the original function, generating a resulting safe path. The
attractiveness of this methodology which makes it look very simple, is
that it neither requires the computation of a projection of the robot position
on the path, nor does it need to consider a moving virtual target
to be tracked. The performance of the proposed approach is analyzed
by means of a series of experiments performed in dynamic environments
with unicycle-type robots by integrating and determining the position of
robot using odometry and in Motion capturing environment.
(ii) We investigate the problem of multi-robot cooperative localization
in dynamic environments. Specifically, we propose an approach where
wheeled robots are localized using the monocular camera embedded in
the head of a Pepper humanoid robot, to the end of minimizing deviations
from their paths and avoiding each other during navigation tasks.
Indeed, position estimation requires obtaining a linear relationship between
points in the image and points in the world frame: to this end, an
Inverse Perspective mapping (IPM) approach has been adopted to transform
the acquired image into a bird eye view of the environment. The
scenario is made more complex by the fact that Pepper\u2019s head is moving
dynamically while tracking the wheeled robots, which requires to consider
a different IPM transformation matrix whenever the attitude (Pitch
and Yaw) of the camera changes. Finally, the IPM position estimate returned
by Pepper is merged with the estimate returned by the odometry
of the wheeled robots through an Extened Kalman Filter. Experiments
are shown with multiple robots moving along different paths in a shared
space, by avoiding each other without onboard sensors, i.e., by relying
only on mutual positioning information.
Software for implementing the theoretical models described above have
been developed in ROS, and validated by performing real experiments
with two types of robots, namely: (i) a unicycle wheeled Roomba robot(commercially available all over the world), (ii) Pepper Humanoid robot
(commercially available in Japan and B2B model in Europe)
IMPLEMENTATION OF A LOCALIZATION-ORIENTED HRI FOR WALKING ROBOTS IN THE ROBOCUP ENVIRONMENT
This paper presents the design and implementation of a human–robot interface capable of evaluating robot localization performance and maintaining full control of robot behaviors in the RoboCup domain. The system consists of legged robots, behavior modules, an overhead visual tracking system, and a graphic user interface. A human–robot communication framework is designed for executing cooperative and competitive processing tasks between users and robots by using object oriented and modularized software architecture, operability, and functionality. Some experimental results are presented to show the performance of the proposed system based on simulated and real-time information. </jats:p
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