Semi-autonomous Mode Research Articles

A novel STPA approach to software safety and security in autonomous maritime systems

With higher autonomy in maritime systems, tasks and responsibilities are moved from the human operator to software, increasing the complexity and the importance of safe and reliable functionality. Software failures, however, may be introduced from the early life cycle phases intentionally or unintentionally, and these must therefore be mitigated by safe and secure design approaches. A challenge is that existing methods are not particularly well-suited for analyzing software risks. Thus, the objective of this paper is to propose a systematic and efficient software failure identification approach by extending the Systems-Theoretic Process Analysis (STPA) with a software failure taxonomy and the System Modeling Language (SysML). This enables the control structure in STPA to cover both the dynamic and static aspects of the software functions. Combined with an implementation platform independent questionnaire, this gives a more systematic and guided search for potential software failures than existing approaches. To demonstrate the proposed approach, a case study on a ferry's navigation system that operates in manual control or semi-autonomous mode is performed. In the case study, the focus is on creating an avoidance map data structure, including both moving and static obstacles to be avoided by the ferry, and the subsequent process of collision risk warning calculation. Software failures are identified and evaluated in collision scenarios where the ferry operates under foggy conditions. The paper shows that the proposed systematic approach provides an improved process for identifying and analyzing critical software failures. This facilitates enhanced risk mitigation in the design and testing phases contributing to autonomous systems' safety and security.

GoBot Go! Using a Custom Assistive Robot to Promote Physical Activity in Children.

Children worldwide are becoming increasingly inactive, leading to significant wellness challenges. Initial findings from our research team indicate that robots could potentially provide a more effective approach (compared to other age-appropriate toys) for encouraging physical activity in children. However, the basis of this past work relied on either interactions with groups of children (making it challenging to isolate specific factors that influenced activity levels) or a preliminary version of results of the present study (which centered on just a single more exploratory method for assessing child movement). This paper delves into more controlled interactions involving a single robot and a child participant, while also considering observations over an extended period to mitigate the influence of novelty on the study outcomes. We discuss the outcomes of a two-month-long deployment, during which [Formula: see text] participants engaged with our custom robot, GoBot, in weekly sessions. During each session, the children experienced three different conditions: a teleoperated robot mode, a semi-autonomous robot mode, and a control condition in which the robot was present but inactive. Compared to our past related work, the results expanded our findings by confirming with greater clout (based on multiple data streams, including one more robust measure compared to the past related work) that children tended to be more physically active when the robot was active, and interestingly, there were no significant differences between the teleoperated and semi-autonomous modes in terms of our study measures. These insights can inform future applications of assistive robots in child motor interventions, including the guiding of appropriate levels of autonomy for these systems. This study demonstrates that incorporating robotic systems into play environments can boost physical activity in young children, indicating potential implementation in settings crafted to enhance children's physical movement.

A review on smart robotic wheelchairs with advancing mobility and independence for individuals with disabilities

This research paper presents a comprehensive review of smart robotic wheelchairs and their impact on enhancing mobility and independence for individuals with disabilities. Traditional wheelchairs often impose limitations on users, resulting in reduced freedom of movement and limited accessibility. The emergence of smart robotic wheelchairs offers a promising solution to address these challenges. This paper provides an overview of wheelchair technology, identifies the specific challenges faced by individuals with disabilities, and explores the advantages and limitations of smart robotic wheelchairs through a review of previous research studies. The features and functionalities of smart robotic wheelchairs, including navigation and obstacle avoidance capabilities, autonomous and semi-autonomous modes, and customizable control options, are discussed. User experience and performance evaluation, along with the impact on mobility and independence, are examined. The paper concludes with future directions and recommendations to guide further research and development in this important field, aiming to empower individuals with disabilities and improve their quality of life.

ToF 거리 센서로 주행 모드 전환 인터랙션이 가능한 실내용 스마트 모빌리티 앙고(AngGo) 개발

Many shared mobility services, such as electric scooters and bicycles, are available for outdoor use. However, finding a suitable shared mobility vehicle for indoor environments still presents a significant challenge. In this paper, we propose AngGo, a shared indoor smart mobility vehicle that can move conveniently in indoor spaces and communicate user intentions through interactions. AngGo is a chair-shaped mobility vehicle that has four modes: semi-autonomous driving mode, footplate manual driving mode, joystick manual driving mode, and standby mode. In the semi-autonomous mode, AngGo can search for potential users and navigate indoor spaces using six time-of-flight (ToF) distance sensors. Upon noticing that it was difficult for a user to board a moving AngGo, we developed a two-way mode switching interaction using ToF distance sensors: following and blocking. This allows AngGo to change its mode to the standby mode through certain movements of the user. In the standby mode, when the user boards the AngGo, it switches to the footplate manual driving mode. Thereafter, the user can change AngGo’s mode to the joystick manual mode by pressing a joystick button. We also conducted a user experiment to evaluate the workload of the two methods in terms of switching mode interaction. The results showed no significant difference in workloads. However, based on the interviews, users preferred the following methods to blocking method.

Internet of Things Enabled Intelligent Automation for Smart Home with the Integration of PSO Algorithm and PID Controller

Currently, due to the widespread population growth, there is a widespread concern about an electricity shortage. As a result, smart devices have evolved and gained significant attention to reduce power consumption in home appliances due to electricity shortages. However, it lacks a universal remote control that can control home appliances based on environmental conditions. To overcome these challenges, this study proposed a hardware-based remote-control system that operates both in autonomous and semiautonomous modes to control home appliances based on environmental conditions. In the autonomous mode, the receiver section regulates the parameters under ambient conditions by varying the appliance’s applied voltage levels via a dimmer. The parameters in semiautonomous are monitored by the user via various levels of remote control. A 2.4 GHz RF modem is used to establish wireless personal network (WPAN) communication between the remote and the receiver. In addition, a Wi-Fi modem is built into the receiver to enable internet-based mobile applications to operate appliances. During the MATLAB analysis, a proportional integral derivative (PID) controller with a particle swarm optimization (PSO) method was found as a superior approach to control the home appliance with adequate environmental conditions. It is concluded from the MATLAB study that the PSO-PID controller delivered an energy saving of 14.88% for the heater, 36.9% for the exhaust fan, and 37.49% for the light bulb compared to the conventional appliances.

An Experimental Study on Surveillance Robot Using Raspberry Pi

Recently, robots have been developed to reduce human resources and observation time in a fast, booming, and rapidly growing technology. In this study, a surveillance robot is designed and manufactured to move around a given surrounding, preferably a domestic environment, record video & audio and send the information to the user through a network. The robot is allowed to be controlled wirelessly using Raspberry Pi technology from a location remotely using IoT technology. This sensor-based robot uses the Raspberry Pi with Ethernet, WI-Fi and Bluetooth for networking purposes. Python is chosen as the programming language in both autonomous and semi-autonomous modes. The manufactured robot was experimentally tested. The recorded videos, images and audio are successfully transferred through a WiFi network to the end user. The user could also control and move the robot in different directions for specific demands. The designed simple robot interests users to record and transfer information for the safety of their indoors.

Development of a low-cost teleoperated and semi-autonomous robotic arm

A safe human-robot physical interaction is required when the robot is used to help humans. This can be achieved by introducing a teleoperated robotic arm in which a human can teach the robot before performing tasks remotely. This paper develops and establishes a three-degree-of-freedom robotic arm and teaching pendant. In particular, a flexible robotic arm is operated in two different modes, namely, the teleoperated mode and the semi-autonomous mode. The teleoperated mode is a manual control using a teaching pendant, where the robot arm replicates various movements of the teaching pendant. On the contrary, the semi-autonomous mode allows the robot to execute a task from one point to another point repetitively after at least one training of the teaching pendant. The Arduino Uno board is employed as a microcontroller, and the integrated development environment ( IDE ) software is used to write and upload the computer code. A series of tests in which the robot performs different tasks is recorded to evaluate the accuracy and consistency of the semi-autonomous and teleoperated modes. The results show that the performance of the proposed low-cost teleoperated robotic arm is reliable and safe to perform various tasks based on the teaching pendant.

Shuchi 1.0: Robotic System For Automatic Segregation of Waste & Floor Cleaning

The advancements made in technology of robotics have made the existence of humankind simpler and comfortable. This work aims at developing a robot for waste collection, segregation and floor cleaning for domestic purpose. The robot expedites and eases the floor cleaning process by employing wire- less technologies. Robot movement is controlled by the end-user through an Android application. The Shuchi 1.0 model can also be configured to work in the semi-autonomous mode, requiring minimum intervention from the end-user. The system is fitted with sensors to detect the obstacles then changes the course of its path, mounted with a camera and LCD screen to ensure its effective work- ing. It is also equipped with an automatic waste segregator, which overcomes the need for manual segregation, thus having a positive impact on health and the environment. With these Shuchi 1.0 working features, it seeks to realize the goal of the Swachh Bharat Abhiyan by capitalizing on the technologies of IoT and Robotics.

Autonomous mining dump trucks

Research aim is to reduce the costs of a mining company and the number of accidents by increasing the efficiency of the use of equipment and eliminating the human factor. Research methodology: analysis of possible areas of application of autonomous mining dump trucks and problems associated with this process. Results. Mining is carried out in difficult mining conditions, which makes the presence of people in the working area of the quarry problematic. Mining companies are looking to cut costs and make jobs safer, especially in developed countries with high labor costs. The use of dump trucks with remote and autonomous control systems in open pits makes it possible to increase the safety and efficiency of open pit mining, reduce the influence of the human factor and increase the productivity of mining machines. While human drivers can do their job well, autonomous trucks can drive the exact route every time without getting bored, tired or resting. The car does not need clean air, good visibility and a lunch break. At the same time, mining autonomous dump trucks can be used in remote-controlled, semi-autonomous and autonomous modes, and the driver in them is replaced by a central controller and a local self-management system. The robot does not get tired and does not make mistakes, it can work 24 hours a day. Eliminating human error and regular training improves safety and increases the productivity of a mining operation. Such companies as BelAZ, Komatsu and Caterpillar are the leaders in the production of autonomous mining dump trucks. Conclusions. The introduction of autonomous transportation allows the mining company to actually reduce its operating costs. While autonomous technologies are still in their infancy, they continue to evolve. Complex solutions will be of great interest - centralized systems that allow working with a fleet of autonomous vehicles and other mining equipment. Therefore, this direction today is the most developing and promising, and the use of autonomous dump trucks in the mining industry is no longer a distant prospect, but a reality of today

How does peoples’ perception of control depend on the criticality of a task performed by a robot

AbstractRobot companions are starting to become more common and people are becoming more familiar with devices such as Google Home, Alexa or Pepper, one must wonder what is the optimum way for people to control their devices? This paper presents an investigation into how much direct control people want to have of their robot companion and how dependent this is on the criticality of the tasks the robot performs. A live experiment was conducted in the University of Hertfordshire Robot House, with a robot companion performing four different type of tasks. The four tasks were: booking a doctor’s appointment, helping the user to build a Lego character, doing a dance with the user, and carrying biscuits for the user. The selection of these tasks was based on our previous research to define tasks which were relatively high and low in criticality. The main goal of the study was to find what level of direct control over their robot participants have, and if this was dependent on the criticality of the task performed by the robot. Fifty people took part in the study, and each experienced every task in a random order. Overall, it was found that participants’ perception of control was higher when the robot was performing a task in a semi-autonomous mode. However, for the task “carrying biscuits”, although participants perceived to be more in control with the robot performing the task in a semi-autonomous mode, they actually preferred to have the robot performing the task automatically (where they felt less in control). The results also show that, for the task “booking a doctor’s appointment”, considered to be the most critical of all four tasks, participants did not prefer that the robot chose the date of the appointment as they felt infantilised.

The Design of an Autonomous Underwater Vehicle for Water Quality Monitoring

This paper describes the development of a civilian-used autonomous underwater vehicle (AUV) for water quality monitoring at reservoirs and watercourses that can obtain realtime visual and locational information. The mechanical design was completed with CAD software Solidworks. Four thrusters—two horizontal and two vertical—on board enable the vehicle to surge, heave, yaw, and pitch. A specialized water sample collection compartment is designed to perform water collection at target locations. The vehicle has a central controller—STM32—and a sub-coordinate controller—Arduino MEGA 2560—that coordinates multiple sensors including an inertial sensor, ultrasonic sensors, etc. Global Navigation Satellite System (GNSS) and the inertial sensor enable the vehicle’s localization. Remote operators monitor and control the vehicle via a host computer system. Operators choose either semi-autonomous mode in which they set target locations or manual mode. The experimental results show that the vehicle is able to perform well in either mode.

SELF-DRIVING TRANSPORTATION SYSTEM FOR ECO-CAMPUS

In large campuses such as UMS and NTU, students need to move at long distances. The transportation of choice has been public transportation. The most common is in the form of buses. Buses need bus stops at strategic locations and only travel at intervals. Although buses are the most eco-friendly among all the transportation systems within a campus, alternative technologies had been studied to improve it further. Self-driving technologies are the most promising. Combined with sharing technologies such as Uber share, self-driving cars offer the most promising solution. Self-driving technologies are already under active development. Campus application should be the first choice for deployment. Campus environment is a private environment so is well controlled. The maps and network infrastructures are well established so will allow reliable self-driving technologies to be used within the campus only. It is therefore surprising that there are few trials involving self-driving transportation systems in a campus environment. There are various possibilities but all these should be overcome in order to have a truly eco-friendly environment within the campus. Electrical shared self-driving cars allow eco-friendly mass transportation of people because electricity is a clean energy. Sharing allows full utilisation of the vehicles unlike other modes of transportation. Mobile apps and GPS allow pickup of passengers at any safe place instead of just at designated places. Because self-driving cars have no drivers, small vehicles may be used economically without the added costs of an extra non-paying passenger and salary of the driver for each vehicle. The lack of any driver also makes it safer for the students especially female students. Although there are still issues of safety among current self-driving technologies as had been shown by the accidents suffered by Tesla cars running on even semi-autonomous modes, safety within the campus should be much better and there is no need for full certification from the transportation authorities. Operating within the campus environment allow operators to operate without the strict licencing requirements of the public transportation environment. Safety can still be ensured by restricting the operation of the self-driving vehicles within clearly marked roads in the campus, enforcing safe speed limits such as the 50 km/hr imposed by Google and restricting operations in clear weather and daytime only. With remote operators and emergency buttons, even the semi-autonomous modes that are within the capabilities of current hardware, self-driving ride-sharing cars should be possible.

Distributed Energy-Efficient Power Control for Macro–Femto Networks

Femtocell deployment provides a cost- and energy-saving solution for cellular operators. Although energy efficiency is imperative for green communications, most existing works on femtocells focus on interference mitigation and capacity maximization rather than on energy efficiency. In this paper, we propose two energy-efficient power control (EEPC) schemes for downlink transmissions in multichannel macro-femto networks, namely, gradient-based distributed power control (GDPC) and energy-efficient game-based power control (EGPC). In particular, GDPC maximizes energy efficiency by macro base stations (BS) or femto access points (FAPs) operating in a semi-autonomous mode, with partial derivatives and system power information exchanged periodically between neighboring macro BSs or FAPs. To make the power control completely distributed without inter-BS communications, EGPC is further proposed based on game theory, in which each BS updates its power-allocation strategy to maximize its utility. We theoretically prove the existence and uniqueness of equilibrium of the power control game in EGPC. Simulations are carried out based on realistic channel conditions to verify the analytical results and validate the effectiveness of GDPC and EGPC. It is shown that both GDPC and EGPC can effectively improve the system energy efficiency compared with average power allocation (APA) and another two power control schemes (i.e., a distributed power control algorithm and a noncooperative game) and that EGPC can converge to the equilibrium with better performance.

Modeling Teleoperated Robot Driving Performance as a Function of Environment Difficulty

Abstract: Modeling mobile robot driving performance is a challenging task, but a simple, accurate model can be helpful in making robot system design decisions that balance cost and performance. Driving performance can depend on a variety of factors including human ability, capabilities of the physical robot, and characteristics of the robot's environment ( e.g. obstacles, terrain). This paper investigates teleoperated robot driving time for a task that includes obstacles in an environment. We hypothesize that a model analogous to Fitts’ Law can be used to describe robot performance (driving time) as a function of environment difficulty. A new definition of the difficulty index (ID) in Fitts' Law is proposed in this paper that describes an environment's difficulty based on the arrangement of obstacles. The model is tested with data from a human subject study we conducted, in which a simulated differential drive robot was teleoperated through different environments in a manual control mode and semi-autonomous mode (obstacle avoidance). We demonstrate that the model for driving time and our proposed environment difficulty index fit human subject data well for a simple driving task between one pair of obstacles. Additionally, the model is expanded to predict driving time in a more complex environment with multiple pairs of obstacles. The results of this paper provide a building block for predicting teleoperated driving time performance in larger, more complex environments.

Development of a 20 Degrees of Freedom Kid Sized Humanoid Platform with Vision

A humanoid robot is a robot which has anatomy similar to the human body. They are becoming increasingly popular as research platforms, and are well suited for real world applications due to the ease with which humans perform arbitrary tasks in versatile environments. Progress of humanoid robotics is, however, inhibited due to a shortage of affordable platforms with diverse capabilities. In this work, we present a prototype of GATIK-II, a KidSize humanoid robot. This robot prototype is the second in the GATIK series of humanoid robots, and has been developed with sufficient power and capabilities so as to be employed for various applications. It has autonomous capabilities and can effectively function in a foreign environment by employing a HaViMo vision module and inertial measurement units. Alternatively, it can also be controlled in real time and via an android based mobile phone, thus exhibiting semi-autonomous mode of operation.

Amphibious Surveillance Robot with Smart Sensor Nodes

Robots have been widely used to perform variety of tasks which reduces the manual work specifically in remote areas where human accessibility is unimaginable. The main applications where the robots have exhibited their excellence include surveillance, tracking targets for military purposes and also for disaster management like searching and rescuing victims. This paper deals about an evolutionary Non-humanoid robot for surveillance with intruder protection capability. The unique feature of this surveillance robot is that it can travel both on land and water and is equipped with robotic arm to handle the work safely. It is armed with a low power high performance NXP processor which is able to manage power more efficiently. Besides being able to work in Semi-autonomous mode, the CCD (Charge Coupled Devices) along with camera aids the operator to control it in manual mode

Amphibious Surveillance Robot with Smart Sensor Nodes

Robots have been widely used to perform variety of tasks which reduces the manual work specifically in remote areas where human accessibility is unimaginable. The main applications where the robots have exhibited their excellence include surveillance, tracking targets for military purposes and also for disaster management like searching and rescuing victims. This paper deals about an evolutionary Non-humanoid robot for surveillance with intruder protection capability. The unique feature of this surveillance robot is that it can travel both on land and water and is equipped with robotic arm to handle the work safely. It is armed with a low power high performance NXP processor which is able to manage power more efficiently. Besides being able to work in Semi-autonomous mode, the CCD (Charge Coupled Devices) along with camera aids the operator to control it in manual mode

A pure vision-based topological SLAM system

In this paper, we present a feasible solution to the problem of autonomous navigation in initially unknown environments using a pure vision-based approach. The mobile robot performs range sensing with a unique omnidirectional stereovision system, estimates its motion using visual odometry and detects loop closures via a place recognition system as it performs topological map building and localization concurrently. Owing to the importance of performing loop closing regularly, the mobile robot is equipped with an active loop closure detection and validation system that assists it to return to target loop closing locations, validates ambiguous loop closures and provides it with the ability to overturn the decision of an incorrectly committed loop closure. A refined incremental probabilistic framework for an appearance-based place recognition system is fully described and the final system is validated in multiple experiments conducted in indoor, semi-outdoor and outdoor environments. Lastly, the performance of the probabilistic framework is compared with the rank-based framework with additional experiments conducted in the semi-autonomous mode, where the mobile robot, provided with a priori information in the form of a topological map that is built in a separate occasion in an offline manner, is required to reach its target destination.

ON THE REDEFINITION OF FAN OUT METRIC FOR HUMAN ROBOT INTERACTIONS WITH HUMANOID SOCCER ROBOTS

Fan out (FO) is adopted as a general index among human robot interaction researchers in predicting the maximum number of robots a single operator can handle simultaneously while maintaining performance at acceptable levels. Neglect tolerance model forms the basis for FO metric that assumes ideal conditions wherein the operator switches control between robots sequentially based on acceptable performance ignoring any false alarms due to erroneous interactions. In this article, we redefine the FO metric to account for any additional demands due to the occurrence of false alarms, as these additional demands could lead to task failure. Experiments with our virtual and real humanoid soccer robots across tele-operation and semi-autonomous modes of autonomy showed significant drop in FO predictions with inclusion of demands due to false alarms for all experimental cases.

Field Trial of a Networked Robot at a Train Station

We developed a networked robot system in which ubiquitous sensors support robot sensing and a human operator processes the robot’s decisions during interaction. To achieve semi-autonomous operation for a communication robot functioning in real environments, we developed an operator-requesting mechanism that enables the robot to detect situations that it cannot handle autonomously. Therefore, a human operator helps by assuming control with minimum effort. The robot system consists of a humanoid robot, floor sensors, cameras, and a sound-level meter. For helping people in real environments, we implemented such basic communicative behaviors as greetings and route guidance in the robot and conducted a field trial at a train station to investigate the robot system’s effectiveness. The results attest to the high acceptability of the robot system in a public space and also show that the operator-requesting mechanism correctly requested help in 84.7% of the necessary situations; the operator only had to control 25% of the experiment time in the semi-autonomous mode with a robot system that successfully guided 68% of the visitors.