Intelligent strategies for mobile robotics in laboratory automation

In this thesis a new intelligent framework is presented for the mobile robots in laboratory automation, which includes: a new multi-floor indoor navigation method is presented and an intelligent multi-floor path planning is proposed; a new signal filtering method is presented for the robots to forecast their indoor coordinates; a new human feature based strategy is proposed for the robot-human smart collision avoidance; a new robot power forecasting method is proposed to decide a distributed transportation task; a new blind approach is presented for the arm manipulations for the robots

Overview of Battery Monitoring and Recharging of Autonomous Mobile Robot

Mobile robots should be capable of operating with a great degree of autonomy to operate in real social environments. Mobile robotic systems draw power from batteries which have a limited power life. This poses a greater challenge for an autonomous robot. Monitoring the status of the battery power in the robot is therefore important for autonomous robotic systems. Docking and recharging are crucial abilities of autonomous mobile robot to ensure its performance. In this paper, the focus of attention is on the significance of power monitoring for long-term operation of autonomous robots and power estimation and auto-recharging. This paper attempts to brief about a literature review of complete solution for docking methods and recharging the battery of a mobile robot. Major progress is being done on both technology and exploitation of docking mechanism and recharging without any human intervention. This review paper gives the overview of related work in terms of immediate challenges for true energy autonomy in mobile robots with respect to battery technology, power estimation and auto recharging

Fast return path planning for agricultural autonomous terrestrial robot in a known field

The agricultural sector is becoming more critical than ever in view of the expected overpopulation of the Earth. The introduction of robotic solutions in this field is an increasingly researched topic to make the most of the Earth's resources, thus going to avoid the problems of wear and tear of the human body due to the harsh agricultural work, and open the possibility of a constant careful processing 24 hours a day. This project is realized for a terrestrial autonomous robot aimed to navigate in an orchard collecting fallen peaches below the trees. When it receives the signal indicating the low battery, it has to return to the docking station where it will replace its battery and then return to the last work point and resume its routine. Considering a preset path in orchards with tree rows with variable length by which the robot goes iteratively using the algorithm D*. In case of low battery, the D* algorithm is still used to determine the fastest return path to the docking station as well as to come back from the docking station to the last work point. MATLAB simulations were performed to analyze the flexibility and adaptability of the developed algorithm. The simulation results show an enormous potential for adaptability, particularly in view of the irregularity of orchard field, since it is not flat and undergoes modifications over time from fallen branch as well as from other obstacles and constraints. The D* algorithm determines the best route in spite of the irregularity of the terrain. Moreover, in this work, it will be shown a possible solution to improve the initial points tracking and reduce time between movements.Project PrunusBot - Sistema robótico aéreo autónomo de pulverização controlada e previsão de produção frutícola (autonomous unmanned aerial robotic system for controlled spraying and prediction of fruit production), Operation n.º PDR2020-101-031358 (leader), Consortium n.º 340, Initiative n.º 140 promoted by PDR2020 and co-financed by FEADER under the Portugal 2020 initiative.info:eu-repo/semantics/publishedVersio

Routing algorithm for the ground team in transmission line inspection using unmanned aerial vehicle

With the rapid development of robotics technology, robots are increasingly used to conduct various tasks by utility companies. An unmanned aerial vehicle (UAV) is an efficient robot that can be used to inspect high-voltage transmission lines. UAVs need to stay within a data transmission range from the ground station and periodically land to replace the battery in order to ensure that the power system can support its operation. A routing algorithm must be used in order to guide the motion and deployment of the ground station while using UAV in transmission line inspection. Most existing routing algorithms are dedicated to pathfinding for a single object that needs to travel from a given start point to end point and cannot be directly used for guiding the ground station deployment and motion since multiple objects (i.e., the UAV and the ground team) whose motions and locations need to be coordinated are involved. In this thesis, we intend to explore the routing algorithm that can be used by utility companies to effectively utilize UAVs in transmission line inspection. Both heuristic and analytical algorithms are proposed to guide the deployment of the ground station and the landing point for UAV power system change. A case study was conducted to validate the effectiveness of the proposed routing algorithm and examine the performance and cost-effectiveness --Abstract, page iii

An investigation of service degradation in long-term human-robot interaction with a particular reference to recharge behaviour

Autonomous long-term operation of social robots has always been a challenge in Human robot-interaction. Social mobile robots acting as companions or assistants will need to operate over a long-term period of time (days, weeks or even months) to perform daily tasks and interact with users. Therefore they should be capable of operating with a great degree of autonomy and will require sustainable social intelligence. Social robots are fallible and have their own limitations with the service they provide. One of the most important limitations of mobile robots is power constraints and the need for frequent recharging. Social mobile robots generally draw power from batteries carried on the robot in order to operate various sensors, actuators and perform tasks. However, batteries have a limited power life and take a long time to recharge via a power source. While the recharge behaviour is active, which may impede human-robot interaction and lead to service degradation. This thesis raises some important issues related to recharge behaviour of social mobile robots which appear to have been overlooked in social robotics research. This work investigated service degradation in long-term interaction due to recharge behaviour of autonomous social mobile robots and proposes an approach to manage service degradation due to recharge. First we performed a long-term study to investigate the service degradation caused by the recharging behaviour of a social robot. Second we conducted a more focused social study which helped to understand user’s attitudes towards a mobile robot with respect to recharge activity. We explored a social strategy by modifying the robot’s verbal behaviour to manage service degradation during recharge. The results obtained from our social study indicates the use of verbal strategies (transparency, apology, politeness) made the robot more acceptable to the users during recharge. We believe that social mobile robots should behave in a socially intelligent manner while managing service degradation. We also provide some recommendations for social mobile robots to manage their recharge behaviour in this thesis

Challenges and Solutions for Autonomous Robotic Mobile Manipulation for Outdoor Sample Collection

In refinery, petrochemical, and chemical plants, process technicians collect uncontaminated samples to be analyzed in the quality control laboratory all time and all weather. This traditionally manual operation not only exposes the process technicians to hazardous chemicals, but also imposes an economical burden on the management. The recent development in mobile manipulation provides an opportunity to fully automate the operation of sample collection. This paper reviewed the various challenges in sample collection in terms of navigation of the mobile platform and manipulation of the robotic arm from four aspects, namely mobile robot positioning/attitude using global navigation satellite system (GNSS), vision-based navigation and visual servoing, robotic manipulation, mobile robot path planning and control. This paper further proposed solutions to these challenges and pointed the main direction of development in mobile manipulation