In this paper, we consider the problem of autonomous navigation with a micro aerial vehicle (MAV) in indoor environments. In particular, we are interested in autonomous navigation in buildings with multiple floors. To ensure that the robot is fully autonomous, we require all computation to occur on the robot without need for external infrastructure, communication, or human interaction beyond high-level commands. Therefore, we pursue a system design and methodology that enables autonomous navigation with real-time performance on a mobile processor using only onboard sensors. Specifically, we address multi-floor mapping with loop closure, localization, planning, and autonomous control, including adaptation to aerodynamic effects during traversal through spaces with low vertical clearance or strong external disturbances. We present experimental results with ground truth comparisons and performance analysis.

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Autonomous multi-floor indoor navigation with a computationally constrained MAV

Computer vision is a rapidly growing field devoted to analyzing, modifying, and high-level understanding of images. Its objective is to determine what is happening in front of a camera and use that understanding to control a computer or robotic system, or to provide people with new images that are more informative or aesthetically pleasing than the original camera images. Application areas for computer-vision technology include video surveillance, biometrics, automotive, photography, movie production, Web search, medicine, augmented reality gaming, new user interfaces, and many more.

Real-time computer vision with OpenCV

Designing controllers for tasks with complex nonlinear dynamics is extremely challenging, time-consuming, and in many cases, infeasible. This difficulty is exacerbated in tasks such as robotic food-cutting, in which dynamics might vary both with environmental properties, such as material and tool class, and with time while acting. In this work, we present DeepMPC, an online real-time model-predictive control approach designed to handle such difficult tasks. Rather than hand-design a dynamics model for the task, our approach uses a novel deep architecture and learning algorithm, learning controllers for complex tasks directly from data. We validate our method in experiments on a large-scale dataset of 1488 material cuts for 20 diverse classes, and in 450 real-world robotic experiments, demonstrating significant improvement over several other approaches.

/pdf/deepmpc-learning-deep-latent-features-for-model-predictive-55dg3p411u.pdf

DeepMPC: Learning Deep Latent Features for Model Predictive Control

We describe the Lightweight Communications and Marshalling (LCM) library for message passing and data marshalling. The primary goal of LCM is to simplify the development of low-latency message passing systems, especially for real-time robotics research applications.

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LCM: Lightweight Communications and Marshalling

This paper presents MORSE, a new open-source robotics simulator. MORSE provides several features of interest to robotics projects: it relies on a component-based architecture to simulate sensors, actuators and robots; it is flexible, able to specify simulations at variable levels of abstraction according to the systems being tested; it is capable of representing a large variety of heterogeneous robots and full 3D environments (aerial, ground, maritime); and it is designed to allow simulations of multiple robots systems. MORSE uses a “Software-in-the-Loop” philosophy, i.e. it gives the possibility to evaluate the algorithms embedded in the software architecture of the robot within which they are to be integrated. Still, MORSE is independent of any robot architecture or communication framework (middleware). MORSE is built on top of Blender, using its powerful features and extending its functionality through Python scripts. Simulations are executed on Blender's Game Engine mode, which provides a realistic graphical display of the simulated environments and allows exploiting the reputed Bullet physics engine. This paper presents the conception principles of the simulator and some use-case illustrations.

/pdf/modular-open-robots-simulation-engine-morse-45gztl83s4.pdf

Modular open robots simulation engine: MORSE

The utility model relates to a robot operating system. A display screen is arranged inside and connected with a control box through a data line. In this way, the robot operating system is designed to be in an integrated structure. Both ends of the upper cap of the control box on the outer side are provided with lock catches respectively. After the control box is covered, the security of the upper cap and the lower cap of the control box is improved; the outer surface of the control box is provided with a handle so that the entire control box can be carried conveniently. Radiator fans are arranged on the left side and the right side of the control box respectively, and are used for radiating the heat generated inside the control box. The robot operating system is designed simply and reasonably as a whole; the entire control box is made of shock-proof and heat-proof material, and can protect the parts inside well. Accordingly, besides improving the safety, the robot operating system can be carried conveniently.

Robot operating system

The utility model relates to an electric flexible axle cleaning machine. A variable frequency type motor is connected with a power output opening and one end of a driving flexible axle in sequence, and the other end of the driving flexible axle is fixedly connected with a brush sweeper to ensure the variable frequency type motor to flexibly and conveniently control the rotating direction and the rotating speed of the brush. Because the main body of the driving flexible axle adopts the spring design, the brush can sweep in a bent pipeline. The electric flexible axle cleaning machine has the advantages that the overall design structure is simple and reasonable, the connection of all the components is compact, the carryover is convenient, the installation is simple, and thereby the electric flexible axle cleaning machine is applied to the sweeping operation for the inner part of any pipeline.

Xiaoxue Zhong

Papers

Robot operating system

Electric soft shaft washer