Developing a low-cost beer dispensing robotic system for the service industry

As the prices of commercially available electronic and mechanical components decrease, manufacturers such as Devantech and Revolution Education have made encoded motor controller systems and microcontrollers very accessible to engineers and designers. This has made it possible to design sophisticated robotic and mechatronic systems very rapidly and at relatively low cost. A recent project in the Autonomous Systems Lab at Middlesex University, UK was to design and build a small, automated, robotic bartender based around the 5 litre Heineken 'Draughtkeg' system, which is capable of patrolling a bar and dispensing beer when signalled to by a customer. Because the system was designed as a commercial product, design constraints focused on keeping the build cost down, and so electronic components were sourced from outside companies and interfaced with a bespoke chassis and custom mechanical parts designed and manufactured on site at the University. All the programming was conducted using the proprietary BASIC language, which is freely available from the PicAXE supplier at no cost. This paper will discuss the restrictions involved in building a robot chassis around 'off-theshelf' components, and the issues arising from making the human-machine interaction intuitive whilst only using low-cost ultrasonic sensors. Programming issues will also be discussed, such as the control of accuracy when interfacing a PicAXE microcontroller with a Devantech MD25 Motor Controller board. Public live testing of the system was conducted at the Kinetica Art Fair 2010 event in London and has since been picked up by websites such as Engadget.com and many others. Feedback on the system will be described, as well as the refinements made as a result of these test

Decentralized collaborative transport of fabrics using micro-UAVs

Small unmanned aerial vehicles (UAVs) have generally little capacity to carry payloads. Through collaboration, the UAVs can increase their joint payload capacity and carry more significant loads. For maximum flexibility to dynamic and unstructured environments and task demands, we propose a fully decentralized control infrastructure based on a swarm-specific scripting language, Buzz. In this paper, we describe the control infrastructure and use it to compare two algorithms for collaborative transport: field potentials and spring-damper. We test the performance of our approach with a fleet of micro-UAVs, demonstrating the potential of decentralized control for collaborative transport.Comment: Submitted to 2019 International Conference on Robotics and Automation (ICRA). 6 page

Learning to Fly by Crashing

How do you learn to navigate an Unmanned Aerial Vehicle (UAV) and avoid obstacles? One approach is to use a small dataset collected by human experts: however, high capacity learning algorithms tend to overfit when trained with little data. An alternative is to use simulation. But the gap between simulation and real world remains large especially for perception problems. The reason most research avoids using large-scale real data is the fear of crashes! In this paper, we propose to bite the bullet and collect a dataset of crashes itself! We build a drone whose sole purpose is to crash into objects: it samples naive trajectories and crashes into random objects. We crash our drone 11,500 times to create one of the biggest UAV crash dataset. This dataset captures the different ways in which a UAV can crash. We use all this negative flying data in conjunction with positive data sampled from the same trajectories to learn a simple yet powerful policy for UAV navigation. We show that this simple self-supervised model is quite effective in navigating the UAV even in extremely cluttered environments with dynamic obstacles including humans. For supplementary video see: https://youtu.be/u151hJaGKU

Teleoperating a mobile manipulator and a free-flying camera from a single haptic device

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThe paper presents a novel teleoperation system that allows the simultaneous and continuous command of a ground mobile manipulator and a free flying camera, implemented using an UAV, from which the operator can monitor the task execution in real-time. The proposed decoupled position and orientation workspace mapping allows the teleoperation from a single haptic device with bounded workspace of a complex robot with unbounded workspace. When the operator is reaching the position and orientation boundaries of the haptic workspace, linear and angular velocity components are respectively added to the inputs of the mobile manipulator and the flying camera. A user study on a virtual environment has been conducted to evaluate the performance and the workload on the user before and after proper training. Analysis on the data shows that the system complexity is not an obstacle for an efficient performance. This is a first step towards the implementation of a teleoperation system with a real mobile manipulator and a low-cost quadrotor as the free-flying camera.Accepted versio