45,020 research outputs found
Low computational-cost detection and tracking of dynamic obstacles for mobile robots with RGB-D cameras
Deploying autonomous robots in crowded indoor environments usually requires
them to have accurate dynamic obstacle perception. Although plenty of previous
works in the autonomous driving field have investigated the 3D object detection
problem, the usage of dense point clouds from a heavy LiDAR and their high
computation cost for learning-based data processing make those methods not
applicable to small robots, such as vision-based UAVs with small onboard
computers. To address this issue, we propose a lightweight 3D dynamic obstacle
detection and tracking (DODT) method based on an RGB-D camera, which is
designed for low-power robots with limited computing power. Our method adopts a
novel ensemble detection strategy, combining multiple computationally efficient
but low-accuracy detectors to achieve real-time high-accuracy obstacle
detection. Besides, we introduce a new feature-based data association method to
prevent mismatches and use the Kalman filter with the constant acceleration
model to track detected obstacles. In addition, our system includes an optional
and auxiliary learning-based module to enhance the obstacle detection range and
dynamic obstacle identification. The users can determine whether or not to run
this module based on the available computation resources. The proposed method
is implemented in a small quadcopter, and the experiments prove that the
algorithm can make the robot detect dynamic obstacles and navigate dynamic
environments safely.Comment: 8 pages, 12 figures, 2 table
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
Robot Excitation Trajectories for Dynamic Parameter Estimation using Optimized B-Splines
In this paper we adressed the problem of finding
exciting trajectories for the identification of manipulator link
inertia parameters. This can be formulated as a constraint
nonlinear optimization problem. The new approach in the
presented method is the parameterization of the trajectories
with optimized B-splines. Experiments are carried out on a
7 joint Light-Weight robot with torque sensoring in each
joint. Thus, unmodeled joint friction and noisy motor current
measurements must not be taken into account. The estimated
dynamic model is verified on a different validation trajectory.
The results show a clear improvement of the estimated dynamic
model compared to a CAD-valued model
UltraSwarm: A Further Step Towards a Flock of Miniature Helicopters
We describe further progress towards the development of a
MAV (micro aerial vehicle) designed as an enabling tool to investigate aerial flocking. Our research focuses on the use of low cost off the shelf vehicles and sensors to enable fast prototyping and to reduce development costs. Details on the design of the embedded electronics and the
modification of the chosen toy helicopter are presented, and the technique used for state estimation is described. The fusion of inertial data through an unscented Kalman filter is used to estimate the helicopter’s state, and this forms the main input to the control system. Since no detailed dynamic model of the helicopter in use is available, a method is proposed for automated system identification, and for subsequent controller design based on artificial evolution. Preliminary results obtained with a dynamic simulator of a helicopter are reported, along with some encouraging results for tackling the problem of flocking
Fault-tolerant formation driving mechanism designed for heterogeneous MAVs-UGVs groups
A fault-tolerant method for stabilization and navigation of 3D heterogeneous formations is proposed in this paper. The presented Model Predictive Control (MPC) based approach enables to deploy compact formations of closely cooperating autonomous aerial and ground robots in surveillance scenarios without the necessity of a precise external localization. Instead, the proposed method relies on a top-view visual relative localization provided by the micro aerial vehicles flying above the ground robots and on a simple yet stable visual based navigation using images from an onboard monocular camera. The MPC based schema together with a fault detection and recovery mechanism provide a robust solution applicable in complex environments with static and dynamic obstacles. The core of the proposed leader-follower based formation driving method consists in a representation of the entire 3D formation as a convex hull projected along a desired path that has to be followed by the group. Such an approach provides non-collision solution and respects requirements of the direct visibility between the team members. The uninterrupted visibility is crucial for the employed top-view localization and therefore for the stabilization of the group. The proposed formation driving method and the fault recovery mechanisms are verified by simulations and hardware experiments presented in the paper
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