Feedback Motion Prediction for Safe Unicycle Robot Navigation

As a simple and robust mobile robot base, differential drive robots that can be modelled as a kinematic unicycle find significant applications in logistics and service robotics in both industrial and domestic settings. Safe robot navigation around obstacles is an essential skill for such unicycle robots to perform diverse useful tasks in complex cluttered environments, especially around people and other robots. Fast and accurate safety assessment plays a key role in reactive and safe robot motion design. In this paper, as a more accurate and still simple alternative to the standard circular Lyapunov level sets, we introduce novel conic feedback motion prediction methods for bounding the close-loop motion trajectory of the kinematic unicycle robot model under a standard unicycle motion control approach. We present an application of unicycle feedback motion prediction for safe robot navigation around obstacles using reference governors, where the safety of a unicycle robot is continuously monitored based on the predicted future robot motion. We investigate the role of motion prediction on robot behaviour in numerical simulations and conclude that fast and accurate feedback motion prediction is key for fast, reactive, and safe robot navigation around obstacles.Comment: 11 pages, 5 figures, extended version of a paper submitted to a conference publicatio

Design of Autonomous Cleaning Robot

Today, the research is concentrated on designing and developing robots to address the challenges of human life in their everyday activities. The cleaning robots are the class of service robots whose demands are increasing exponentially. Nevertheless, the application of cleaning robots is confined to smaller areas such as homes. Not much autonomous cleaning products are commercialized for big areas such as schools, hospitals, malls, etc. In this thesis, the proof of concept is designed for the autonomous floor-cleaning robot and autonomous board-cleaning robot for schools. A thorough background study is conducted on domestic service robots to understand the technologies involved in these robots. The components of the vacuum cleaner are assembled on a commercial robotic platform. The principles of vacuum cleaning technology and airflow equations are employed for the component selection of the vacuum cleaner. As the autonomous board-cleaning robot acts against gravity, a magnetic adhesion is used to adhere the robot to the classroom board. This system uses a belt drive mechanism to manoeurve. The use of belt drive increases the area of magnetic attraction while the robot is in motion. A semi-systematic approach using patterned path planning techniques for the complete coverage of the working environment is discussed in this thesis. The outcome of this thesis depicts a new and conceptual mechanical design of an autonomous floor-cleaning robot and an autonomous board-cleaning robot. This evidence creates a preliminary design for proof-of-concept for these robots. This proof of concept design is developed from the basic equations of vacuum cleaning technology, airflow and magnetic adhesion. A general overview is discussed for collaborating the two robots. This research provides an extensive initial step to illustrate the development of an autonomous cleaning robot and further validates with quantitative data discussed in the thesis

Path planning for socially-aware humanoid robots

Designing efficient autonomous navigation systems for mobile robots involves consideration of the robotís environment while arriving at a systems architecture that trades off multiple constraints. We have architected a navigation framework for socially-aware autonomous robot navigation, using only the on-board computing resources. Our goal is to foster the development of several important service robotics applications using this platform. Our framework allows a robot to autonomously navigate in indoor environments while accounting for people (i.e., estimating the path of all individuals in the environment), respecting each individualís private space. In our design, we can leverage a wide number of sensors for navigation, including cameras, 2D and 3D scanners, and motion trackers. When designing our sensor system, we have considered that mobile robots have limited resources (i.e., power and computation) and that some sensors are costlier than others (e.g., cameras and 3D scanners stream data at high rates), requiring intensive computation to provide useful insight for real-time navigation. We tradeoff between accuracy, responsiveness, and power, and choose a Hokuyo UST-20LX 2D laser scanner for robot localization, obstacle detection and people tracking. We use an MPU-6050 for motion tracking. Our navigation framework features a low-power sensor system (< 5W) tailored for improved battery life in robotic applications while providing sufficient accuracy. We have completed a prototype for a Human Support Robot using the available onboard computing devices, requiring less than 60W to run. We estimate we can obtain similar performance, while reducing power by ~60%, utilizing low-power high-performance accelerator hardware and parallelized software.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

A mosaic of eyes

Autonomous navigation is a traditional research topic in intelligent robotics and vehicles, which requires a robot to perceive its environment through onboard sensors such as cameras or laser scanners, to enable it to drive to its goal. Most research to date has focused on the development of a large and smart brain to gain autonomous capability for robots. There are three fundamental questions to be answered by an autonomous mobile robot: 1) Where am I going? 2) Where am I? and 3) How do I get there? To answer these basic questions, a robot requires a massive spatial memory and considerable computational resources to accomplish perception, localization, path planning, and control. It is not yet possible to deliver the centralized intelligence required for our real-life applications, such as autonomous ground vehicles and wheelchairs in care centers. In fact, most autonomous robots try to mimic how humans navigate, interpreting images taken by cameras and then taking decisions accordingly. They may encounter the following difficulties

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