Low-cost Robot Research Articles

Multirobot Object Transport via Robust Caging

In this paper, we propose a control algorithm to collectively transport an object using a group of relatively low-cost robots. We address this problem using the robust caging , which features reliable object closure with minimum number of robots, and requires no high-precision control capability on the individual robot. Given a 2-D convex object, the proposed method uses the quality of complete robustness to first optimize the number of robots in the initial formation, and then reorient and move the formation. The method is free of force analysis, and therefore less prone to sensor errors and failures. Compared with state-of-the-art multirobot object transport approaches, which require more robots and rely heavily on high-precision control, such as force and torque feedback control, our method uses fewer robots and has high tolerance to control noises. We performed both simulation and real-time experiments to demonstrate the performance of our method. We conclude that the proposed robust caging is promising under reduced number of robots and a certain level of control noises in multirobot object transport tasks.

Open Vision System for Low-Cost Robotics Education

Vision devices are currently one of the most widely used sensory elements in robots: commercial autonomous cars and vacuum cleaners, for example, have cameras. These vision devices can provide a great amount of information about robot surroundings. However, platforms for robotics education usually lack such devices, mainly because of the computing limitations of low cost processors. New educational platforms using Raspberry Pi are able to overcome this limitation while keeping costs low, but extracting information from the raw images is complex for children. This paper presents an open source vision system that simplifies the use of cameras in robotics education. It includes functions for the visual detection of complex objects and a visual memory that computes obstacle distances beyond the small field of view of regular cameras. The system was experimentally validated using the PiCam camera mounted on a pan unit on a Raspberry Pi-based robot. The performance and accuracy of the proposed vision system was studied and then used to solve two visual educational exercises: safe visual navigation with obstacle avoidance and person-following behavior.

Low-Power Centimeter-Level Localization for Indoor Mobile Robots Based on Ensemble Kalman Smoother Using Received Signal Strength

How to provide a low-cost but accurate localization solution for the indoor mobile robots are essential in many Internet of Things applications, such as smart home and asset tracking. To achieve this goal, this paper originally proposes a modified two-filter smoother based on ensemble Kalman filter (KF) (denoted as EnKS) for the localization of indoor mobile robots. The proposed EnKS algorithm consists of both a forward part of an ensemble KF (EnKF) with statistical linear regression and a backward part of a modified information KF with state error vector. The EnKS based on stochastic sampling with ensemble members can achieve better positioning accuracy than other Kalman smoothers. When compared to EnKF, the proposed EnKS combines a backward filter to compensate for the estimation error of EnKF and further improves the accuracy. Furthermore, the implementation of the proposed EnKS is conducted in the real world visible light positioning (VLP) system using pre-existing LED lights for low-cost robot localization. To make a performance comparison, this paper also uses baseline smoothers based on extended KF and central difference KF in the VLP system. Preliminary experimental results imply that the proposed EnKS is able to achieve the best positioning accuracy, as high as 11.18 cm on average, but with a comparable computational complexity, which enables to meet the demands of many robot applications.

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Towards rich motion skills with the lightweight quadruped robot Serval

Bio-inspired robotic designs introducing and benefiting from morphological aspects present in animals allowed the generation of fast, robust, and energy-efficient locomotion. We used engineering tools and interdisciplinary knowledge transferred from biology to build low-cost robots, able to achieve a certain level of versatility. Serval, a compliant quadruped robot with actuated spine and high range of motion in all joints, was developed to address the question of what mechatronic complexity is needed to achieve rich motion skills. In our experiments, the robot presented a high level of versatility (number of skills) at medium speed, with a minimal control effort and, in this article, no usage of its spine. Implementing a basic kinematics-duplication from dogs, we found strengths to emphasize, weaknesses to correct, and made Serval ready for future attempts to achieve more agile locomotion. In particular, we investigated the following skills: walk, trot, gallop, bound (crouched), sidestep, turn with a radius, ascend slopes including flat ground transition, perform single and double step-downs, fall, trot over bumpy terrain, lie/sit down, and stand up.

Artificial intelligence could assist chemists with disabilities

Hoby Wedler remembers his years in graduate school as many computational chemists do: long hours writing code, running calculations, and poring over papers. Unlike many computational chemists, however, Wedler had a constant companion while he did those things—an assistant who could do things like describe figures in the article he was reading. Because Wedler is blind, he needed the support to complete his research. Over the past decade or so—at the same time Wedler was working on his PhD—chemists around the world have been thinking about ways they could take repetitive lab work out of scientists’ hands. These new tools include robots that can move around a lab and operate equipment as a human would, as well as automated systems contained entirely within a fume hood to mix reagents. While large-scale automation has been largely the domain of pharmaceutical companies, low-cost robotics and sensors, combined with more sophisticated artificial intelligence

PiBot: An Open Low-Cost Robotic Platform with Camera for STEM Education

This paper presents a robotic platform, PiBot, which was developed to improve the teaching of robotics with vision to secondary students. Its computational core is the Raspberry Pi 3 controller board, and the greatest novelty of this prototype is the support developed for the powerful camera mounted on board, the PiCamera. An open software infrastructure written in Python language was implemented so that the student may use this camera as the main sensor of the robotic platform. Furthermore, higher-level commands were provided to enhance the learning outcome for beginners. In addition, a PiBot 3D printable model and the counterpart for the Gazebo simulator were also developed and fully supported. They are publicly available so that students and schools without the physical robot or that cannot afford to obtain one, can nevertheless practice, learn and teach Robotics using these open platforms: DIY-PiBot and/or simulated-PiBot.

Low-Cost Design Solutions for Educational Robots

Low-cost robotics, fully integrated in the corporate IT infrastructure, is a requirement in the era of modern industrial automation derived from the Industry 4.0 model. This paper presents a multidisciplinary robotics-based learning (R-BL) project consisting of the development of a modular control architecture and a gripper for small manipulators. The solution, as compared with options available in the current robotic market, is a balance between low-cost devices with industrial robot performance. The project is carried out as part of the Robotics and Mechanisms program, a course in the automation engineering degree program at the University of Brescia in Italy. A 4-axis small-size robot, able to manipulate many kinds of objects, was designed and built by a student team by integrating the controller and the gripper. The controller was implemented using a real-time Raspberry platform by following a modular design concept. The control software is characterized by a short development time. The gripper was advanced to achieve low cost and modularity tradeoffs.

A Low-Cost Monocular Vision-Based Obstacle Avoidance Using SVM and Optical Flow

Development of low-cost robots with the capability to detect and avoid obstacles along their path is essential for autonomous navigation. These robots have limited computational resources and payload capacity. Further, existing direct range-finding methods have the trade-off of complexity against range. In this paper, we propose a vision-based system for obstacle detection which is lightweight and useful for low-cost robots. Currently, monocular vision approaches used in the literature suffer from various environmental constraints such as texture and color. To mitigate these limitations, a novel algorithm is proposed, termed as Pyramid Histogram of Oriented Optical Flow ([Formula: see text]-HOOF), which distinctly captures motion vectors from local image patches and provides a robust descriptor capable of discriminating obstacles from nonobstacles. A support vector machine (SVM) classifier that uses [Formula: see text]-HOOF for real-time obstacle classification is utilized. To avoid obstacles, a behavior-based collision avoidance mechanism is designed that updates the probability of encountering an obstacle while navigating. The proposed approach depends only on the relative motion of the robot with respect to its surroundings, and therefore is suitable for both indoor and outdoor applications and has been validated through simulated and hardware experiments.

Study of Driving Torque through Dynamic Analysis of Robot

These days, the interests on the low-cost handling robots are increasing because it is important to get down the unit cost of production to get the price competitiveness. The robot joint with simple mechanism is more suitable to implement the low-cost robot system as well known. The moving parts of robot have to be designed for simple and robust. But the dynamic characteristics analysis is induced by the robot links because they drive in high acceleration and deceleration. In this reason, the dynamic characteristics analysis of the high-speed robot is very important in the design process. In this paper, the study on robot driving torque analysis of a articulated robot has been done and the research results will be introduced

Multi-Functional Sensing for Swarm Robots Using Time Sequence Classification: HoverBot, an Example.

Scaling up robot swarms to collectives of hundreds or even thousands without sacrificing sensing, processing, and locomotion capabilities is a challenging problem. Low-cost robots are potentially scalable, but the majority of existing systems have limited capabilities, and these limitations substantially constrain the type of experiments that could be performed by robotics researchers. Instead of adding functionality by adding more components and therefore increasing the cost, we demonstrate how low-cost hardware can be used beyond its standard functionality. We systematically review 15 swarm robotic systems and analyse their sensing capabilities by applying a general sensor model from the sensing and measurement community. This work is based on the HoverBot system. A HoverBot is a levitating circuit board that manoeuvres by pulling itself towards magnetic anchors that are embedded into the robot arena. We show that HoverBot’s magnetic field readouts from its Hall-effect sensor can be associated to successful movement, robot rotation and collision measurands. We build a time series classifier based on these magnetic field readouts. We modify and apply signal processing techniques to enable the online classification of the time-variant magnetic field measurements on HoverBot’s low-cost microcontroller. We enabled HoverBot with successful movement, rotation, and collision sensing capabilities by utilising its single Hall-effect sensor. We discuss how our classification method could be applied to other sensors to increase a robot’s functionality while retaining its cost.

Affordance Based Approach to Automatic Program Generation for Industrial Robots in Manufacturing

Due to the increasing demand for flexible and low-cost production, manufacturing solutions involving human robot interaction have become much sought-after. Robotic manufacturers meet the demand with a rising number of low cost robots specifically designed around safety and usability. However, the programming is still based on a tool centric teach-in. This paper discusses an affordance based approach for process programming in industrial manufacturing. Using low level feature detection and a consecutive evaluation, a fast programming method for industrial applications is presented. The paper presents the concept and a prototypic implementation for a welding process. Using the affordance detection, the system is able to identify relevant seams based on an image of the work space. The identified seams are then presented to the user for review with the means of augmented reality. Lastly, the system derives a welding program based on the detected seams. First experiments show promising results concerning programming speed and path accuracy for different work piece shapes and task definitions. Finally, based on the experience gained with the prototype, the outlook discusses the possibilities and further fields for future work.

DroneTrack: Cloud-Based Real-Time Object Tracking Using Unmanned Aerial Vehicles Over the Internet

Low-cost drones represent an emerging technology that opens the horizon for new smart Internet-of-Things (IoT) applications. Recent research efforts in cloud robotics are pushing for the integration of low-cost robots and drones with the cloud and the IoT. However, the performance of real-time cloud robotics systems remains a fundamental challenge that demands further investigation. In this paper, we present DroneTrack, a real-time object tracking system using a drone that follows a moving object over the Internet. The DroneTrack leverages the use of Dronemap planner (DP), a cloud-based system, for the control, communication, and management of drones over the Internet. The main contributions of this paper consist in: (1) the development and deployment of the DroneTrack, a real-time object tracking application through the DP cloud platform and (2) a comprehensive experimental study of the real-time performance of the tracking application. We note that the tracking does not imply computer vision techniques but it is rather based on the exchange of GPS locations through the cloud. Three scenarios are used for conducting various experiments with real and simulated drones. The experimental study demonstrates the effectiveness of the DroneTrack system, and a tracking accuracy of 3.5 meters in average is achieved with slow-speed moving targets.

Task and Design Requirements for an Affordable Mobile Service Robot for Elder Care in an All-Inclusive Care for Elders Assisted-Living Setting

The high cost of elder care combined with the shortage of caregivers lead us to consider how service robots can be affordably leveraged to support the independence of elders and the work of their caregivers and clinicians. Our objective is to gain design insight into tasks older adults desire to accomplish daily in a low-resource, assisted living setting and how an affordable service robot could suit. A need-finding design approach consisting of focus groups and surveys was completed with three stakeholders groups: Elders, Clinicians, and Caregivers. Stakeholders were asked to identify and then prioritize service tasks by importance and frustration. Thirty-six unique high priority tasks were identified. Instrumental activities of daily living, a desire to have their preferences known, leisure activities, and increased opportunities for socialization were the most important tasks that the elders wanted a low-cost mobile service robot to address. Clinicians and caregivers prioritized highly safety-related reminders and assistance in complying with care plans in assessment of elder task needs. Service robots exist that do some, but not all of these desired tasks. An effective and affordable service robot requires design trade-offs in terms of cost, preference and complexity. A low-cost robot targeting reminders, companion walking, hydration and fetching assistance was suggested as an initial prototype. Prototypes may address high priority desires of all stakeholders, but robots that can intervene and affect long-lasting changes in elder care are still needed.

HoverBots: Precise Locomotion Using Robots That Are Designed for Manufacturability

Scaling up robot swarms to collectives of hundreds or even thousands without sacrificing sensing, processing, and locomotion capabilities is a challenging problem. Low-cost robots are potentially scalable but the majority of existing systems have limited capabilities, and these limitations substantially constrain the type of experiments that could be performed by robotics researchers. As an alternative to increasing the quantity of robots by reducing their functionality, we have developed a new technology that delivers increased functionality at low-cost. In this paper we present a comprehensive literature review on the most commonly used locomotion strategies of swarm robotic systems. We introduce a new type of low-friction locomotion—active low-friction locomotion—and we show its first implementation in the HoverBot system. The HoverBot system consists of an air-levitation and magnet table, and a HoverBot agent. HoverBot agents are levitating circuit boards which we have equipped with an array of planar coils and a Hall-effect sensor. The HoverBot agent uses its coils to pull itself towards magnetic anchors that are embedded into a levitation table. These robots: use active low-friction locomotion; consist of only surface-mount components; circumvent actuator calibration; are capable of odometry by using a single Hall-effect sensor; and perform precise movement. We conducted three-hours of experimental evaluation of the HoverBot system in which we observed the system performing more than ten-thousand steps. We also demonstrate formation movement, random collision, and straight collisions with two robots. This study demonstrates that active low-friction locomotion is an alternative to wheeled and slip-stick locomotion in the field of swarm robotics.

An Overview of Simultaneous Localization and Mapping Using Low-Cost Mini Robot Platform

An Overview of Simultaneous Localization and Mapping Using Low-Cost Mini Robot Platform

Visual servoing for low-cost SCARA robots using an RGB-D camera as the only sensor

ABSTRACTVisual servoing with a simple, two-step hand–eye calibration for robot arms in Selective Compliance Assembly Robot Arm configuration, along with the method for simple vision-based grasp planning, is proposed. The proposed approach is designed for low-cost, vision-guided robots, where tool positioning is achieved by visual servoing using marker tracking and depth information provided by an RGB-D camera, without encoders or any other sensors. The calibration is based on identification of the dominant horizontal plane in the camera field of view, and an assumption that all robot axes are perpendicular to the identified plane. Along with the plane parameters, one rotational movement of the shoulder joint provides sufficient information for visual servoing. The grasp planning is based on bounding boxes of simple objects detected in the RGB-D image, which provide sufficient information for robot tool positioning, gripper orientation and opening width. The developed methods are experimentally tested using a real robot arm. The accuracy of the proposed approach is analysed by measuring the positioning accuracy as well as by performing grasping experiments.

Computer Aided Design of a Low-Cost Painting Robot

Computer Aided Design of a Low-Cost Painting Robot

Control of non-linear actuator of artificial muscles for the use in low-cost robotics prosthetics limbs

Currently, the methods of actuating robotic-based prosthetic limbs are moving away from bulky actuators to more fluid materials such as artificial muscles. The main disadvantages of these artificial muscles are their high cost of manufacturing, low-force generation, cumbersome and complex controls. A recent discovery into using super coiled polymer (SCP) proved to have low manufacturing costs, high force generation, compact and simple controls. Nevertheless, the non-linear controls still exists due to the nature of heat-based actuation, which is hysteresis. This makes position control difficult. Using electrically conductive devices allows for very quick heating, but not quick cooling. This research tries to solve the problem by using peltier devices, which can effectively heat and cool the SCP, hence giving way to a more precise control. The peltier device does not actively introduce more energy to a volume of space, which the coiled heating does; instead, it acts as a heat pump. Experiments were conducted to test the feasibility of using peltier as an actuating method on different diameters of nylon fishing strings. Based on these experiments, the performance characteristics of the strings were plotted, which could be used to control the actuation of the string efficiently in the future.

Phogo: A low cost, free and “maker” revisit to Logo

Today it is almost impossible to spend a single day without depending on an information system, a computer or any other form of computation. Though the starting barrier is low, fundamental concepts are still required in order to manage the technicalities of the engineering environment and everyday computational systems. In 1967, Logo proposed to teach abstract programming concepts by providing a set of functions that had intuitive, visible effects over a robotic Turtle. LOGO was a success, but the robots quickly migrated into computer simulations. From LOGO, many followed. Scratch and Lego Mindstorm are some of the most notorious examples. Both introduced graphical block-based programming interfaces. We propose to bring back the powerful ideas behind LOGO by updating it with state of the art technologies. Phogo combines Python, Arduino and 3D printing into a low cost robot that is easy to build and control. The robot has a pen to draw shapes and can be commanded from a computer via a wireless link that is transparent to the students. The use of a physical robot can make programming more accessible for students with disabilities. The open and maker philosophies behind Phogo makes it more interesting as students will be able to access and study the electronic components. The textual programing language can be a long life companion for the students. In this work we discuss LOGO and other projects inspired by it, and we also share the methodology and design decisions behind Phogo, the results of its application in a workshop and the improvements we are currently developing.