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IHRFELT, FREDRIK, and WILLIAM MARIN. "Self-balancing robot : WiFi steerable self-balancing robot." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279821.
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This bachelor thesis aims to investigate the viability of using two wheeled self-balancing robots for package deliveries. The movement of the two wheeled self-balancing robot resembles the human movement more than a traditional four wheeled vehicle. The goal of the report is to build a selfbalancing robot to investigate how far from the center axis a weight can be added, as well as what the response time of a Wireless Fidelity (WiFi) connection for steering the robot is and how it compares to a Bluetooth connection. Balance of the robot was achieved by using a Proportional-IntegralDerivative (PID) controller with inputs from a gyroscope and accelerometer. Stepper motors were used to maneuver the robot. When the robot was constructed tests were performed to evaluate how far from the center axis a weight could be added. A test was also performed to evaluate the WiFi connection response time with regard to the distance between the operator and the robot, as well as the maximum range and how it compares to Bluetooth. The results showed that a one kilogram weight could be added five centimeters from the center axis, that the response time was around 10-20 milliseconds for a distance up to 35 meters. A WiFi connection has a longer range compared to Bluetooth and also has a lower response time.<br>Denna rapport strävar efter att undersöka möjligheterna av att använda en själv-balanserande robot för paketleveranser. Rörelsen av en tvåhjulig själv-balanserande robot liknar den mänskliga rörelsen mer än ett traditionellt fyrhjuligt fordon. Målet med rapporten är att bygga en självbalanserande robot för att undersöka hur långt från dess centeraxel en vikt kan placeras, samt undersöka vilken responstid som uppnås med en Wireless Fidelity (WiFi)-länk och hur en WiFi-länk jämför med en Bluetooth-länk. Balans uppnåddes genom att använda en Proportional-IntegralDerivative (PID) regulator med input från ett gyroskop och en accelerometer. Stegmotorer användes för att manövrera roboten. När roboten hade konstruerats utfördes tester för att undersöka hur långt från centrumaxeln en vikt kunde placeras. Ett test utfördes för att undersöka responstiden för en WiFi-länk med avseende på avståndet mellan operatör och robot, samt att undersöka den maximala räckvidden och jämföra den mot Bluetooth. Resultaten visade att en vikt på ett kilogram kunde placeras fem centimeter från centeraxeln, att responstiden var ungefär 10-20 millisekunder för avstånd upp till 35 meter. En WiFi-länk har en längre räckvidd än Bluetooth och kortare responstid.
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Nguyen, Dan, and Kayan Phuong. "SB-Bot : A Self-Balancing Robot." Thesis, KTH, Maskinkonstruktion (Inst.), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191518.
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It is important to explore the possibilities of sustainable transportation systems in order to achieve a sustainable future. A two-wheeled vehicle, where the wheels are placed parallel to each other, is an option that is of interest to explore. This report explores the problems of modeling and constructing a prototype of a two-wheeled robot that is able to balance on its own. The aim of this thesis was to analyze the performance between theory and the prototype with respect to the rise time. The prototype was limited to independently balance on a flat surface in one direction with small angle deviations. The horizontal movement of all parts was assumed to be equal during balancing and other simplifications were made and justified in the report. The results showed that the rise time of the theoretical model was 0.420 seconds while the prototype’s was 0.451 seconds. The prototype was 0.031 seconds or 7.4% slower than the theoretical model. The reasons for this were discussed and possible sources of error could have been difficulties in calibrating the IMU, not considering the center of gravity in the tilting direction, difference in motors’ actual performance, among other reasons discussed in the report. The causes for the slower performance show room for improvement which could lower the difference to negligible levels unless higher precision is desired. The derived models could also be expanded to control position and velocity. Furthermore the scope can be expanded to handle larger angular deviations, movement in more than one direction and on uneven surfaces. Our thesis is one of the areas that is useful to explore in order to develop a two-wheeled self-balancing vehicle. In combination with further research there are possibilities of a realized product.<br>Det är viktigt att utforska möjligheterna inom hållbara transportmedel för att gå mot en hållbar framtid. Ett två-hjuligt fordon, där hjulen är placerade parallellt i förhållande till varandra, är ett alternativ som är intressant att utforska. Den här rapporten utforskar möjligheterna av modelleringen och konstruktionen av en två-hjuling robot som självständigt kan balansera. Målet med arbetet var att analysera prestationen mellan teorin och prototypen med avseende på stigtiden. Prototypen begränsades till att kunna balansera självständigt på en platt yta i en riktning inom små vinkelförändringar. Alla delar antogs ha samma horisontala rörelse vid balansering och andra förenklingar som gjordes är rättfärdigade i rapporten. Resultaten visade att stigtiden av den teoretiska modellen var 0.451 sekunder medan prototypens stigtid var 0.420 sekunder. Prototypens stigtid var 0.031 sekunder eller 7.4% långsammare än den teoretiska modellen. Skälen till detta diskuterades kunna ligga i svårigheterna att kalibrera IMUn, försummandet av tyngdpunkten i den lutande riktningen, skillnaden i motorernas faktiska prestanda, bland andra skäl som diskuteras i rapporten. Orsakerna till den långsammare stigtiden visar utrymme för förbättring till försumbara nivåer, om högre precision inte är önskat. De härledda modellerna kan också utökas för att reglera position och hastighet. Fortsättningsvis kan arbetets omfattning utvidgas till att hantera större vinkelförändringar, förflyttningen i flera riktningar och ojämna ytor. Vårt arbete är ett av de områden som är användbara att utforska i syfte att utveckla et två-hjuligt balanserande fordon. I kombination med vidare forskning finns möjligheterna av en realiserad produkt.
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Haraldsson, Jonathan, Julia Nordin, and Johanna Blomstedt. "Expressive Arduino Controlled Self-Balancing Robot." Thesis, Uppsala universitet, Fasta tillståndets elektronik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-298757.
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A robot capable of balancing itself on two wheels has been built and programmed. While balancing, the robot keeps within a limited area. The robot has a face with two eyes and a mouth, consisting of LED-matrices, which switch between six different facial expressions. The robot is programmed using Arduino boards, one of which implements PID regulators to control the motors.
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Bosco, Bruno, André Ellnefjärd, Nordenmark Victor Ellqvist, Alexander Hemberg, Henrik Olsson, and Jonas Tegelberg. "Development of a self-balancing two wheeled robot." Thesis, KTH, Maskinkonstruktion (Inst.), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-102054.
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Denna rapport beskriver och förklarar processen för att utforma och konstruera en parallell tvåhjulig robot, lik en Segway, med syfte att tävla mot andra liknande konstruktioner i en tävling. Roboten är konstruerad kring den inverterade pendelns princip och eftersom den är instabil har den aktivt balanserats. En accelerometer och ett gyro har tillsammans med ett Kalmanfiler använts för att bestämma robotens vinkel mot tyngdaccelerationen. När tyngdpunkten flyttas, ger det återkopplade systemet en rörelse i motsatt riktning för att säkerställa balansen. Små korrigeringar är alltid nödvändiga för en stabil position, och dessa har implementerats i en PID-regulator. Flera delsystem har utvecklats och integrerats för att tillgodose behoven för att kunna medverka i tävlingen, såsom en mållinjesensor, ett vapensystem, ett par kodgivare, en set med utfällbara ben, en fjärrkontroll och en text-till-tal-modul. Alla delsystem förutom de utfällbara benen integrerades i den slutliga prototypen. Vid rapportens sammanställande kvarstod endast tävlingsmomentet.<br>This paper presents and explains the process of designing and constructing a parallel two wheeled balancing robot, much like a Segway, with the purpose of competing against other similar designs in a race. The robot is designed around the principal of an inverse pendulum, and because it is always unstable it has to be actively balanced to be able to stand up. An accelerometer and a gyro together with a Kalman filter are used to determine the angle of the robot. When the center of mass starts to tip over, the feedback system moves the robot in the same direction to keep its balance. Small corrections are always needed to be able to stand straight, which has been implemented in the form of a PID-controller. Several subsystems have also been developed or integrated to accommodate the needs to successfully participate in the race, such as a finish line sensor, a weapon system, a pair of encoders, a set of unfolding legs, a remote controller and a text-to-speech module. All subsystems except the unfolding legs were successfully integrated into the finished prototype, but upon completion of this report the finished robot has yet to participate in the competition.
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Eriksson, Emil. "Self-Balancing Robot Control System in CODESYS for Raspberry Pi : Design and Construction of a Self-Balancing Robot using PLC-programming tools." Thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-133990.
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The Department of Applied Physics and Electronics at Umeå University offers education and conducts research in the field of automation and robotics. To raise the competence in automation in the CODESYS development environment it’s proposed to build a remote controlled self-balancing robot as a testing platform which is then programmed using CODESYS for Raspberry Pi. The chassis of the robot consists of laser-cut plexiglass plates, stacked on top of each other and fixed using threaded rods, nuts and washers. On these plates the robots’ electrical components, wheels and motors are attached. The control system is designed as a feedback loop where the robots’ angle relative to the gravity vector is the controlled variable. A PID-controller is used as the system controller and a Kalman Filter is used to filter the input signals from the IMU board using input from both the accelerometer and the gyro. The control system is implemented in CODESYS as a Function Block Diagram (FBD) using both pre-made, standard function blocks and customized function blocks. By using the in-built web-visualization tool the robot can be remote controlled via Wi-Fi. After tuning the Kalman Filter through plot-analysis and the PID-controller through Ziegler-Nichols method the robot can stay balanced on a flat surface. The robots’ performance is tested through a series of test scenarios of which it only completes one out of four. The project ran out of time before further testing could be done. For future work one could improve the performance of the PID-controller through more sophisticated tuning methods. One can also add a steering-function or test different type of controllers.
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Brown, Evan (Evan C. ). "Mechanical design of a jumping and self-balancing monopedal robot." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119961.
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Thesis: S.B., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 59-60).<br>This project involved the design and fabrication of a self-balancing monopedal robot which is intended to be used as a platform for physically validating simulated risk network based control analysis. A precomputed risk network allows a robot to evaluate the risk that an action will lead to an imminent fall or lead to a state from which the robot will eventually fall after several jumps.' The physical implementation of the simulated robot will allow the theoretical boundaries of safety to be validated. If validated, risk matrix analysis will allow a system to be modeled such that the controller can modify control inputs which would lead falls. The results of physical testing will be used to refine the simulated model. The robot was designed to be as simple as possible while still being capable of operating in three dimensions to study hybrid dynamics and underactuated locomotion. A mechanism with a direct kinematic relation to the output along with a static contact area was designed to allow the ground force profiles to be accurately controlled. In order to utilize the risk network, the force applied by the foot as well as the robot's take-off angle and rate of angular rotation at take-off are key parameters which must be measured and controlled. The robot was be optimized to precisely control these parameters rather than to achieve the longest or highest jump possible as is the objective of other studies.<br>by Evan Brown.<br>S.B.
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Robillard, Dominic. "Development of a Stair-Climbing Robot and a Hybrid Stabilization System for Self-Balancing Robots." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31840.
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Self-balancing robots are unique mobile platforms that stay upright on two wheels using a closed-loop control system. They can turn on the spot using differential steering and have compact form factors that limit their required floor space. However they have major limitations keeping them from being used in real world applications: they cannot stand-up on their own, climb stairs, or overcome obstacles. They can fall easily if hit or going onto a slippery surface because they rely on friction for balancing. The first part of this research proposes a novel design to address the above mentioned issues related to stair-climbing, standing-up, and obstacles. A single revolute joint is added to the centre of a four-wheel drive robot onto which an arm is attached, allowing the robot to successfully climb stairs and stand-up on its own from a single motion. A model and simulation of the balancing and stair-climbing process are derived, and compared against experimental results with a custom robot prototype. The second part, a control system for an inverted pendulum equipped with a gyroscopic mechanism, was investigated for integration into self-balancing robots. It improves disturbance rejection during balance, and keeps equilibrium on slippery surfaces. The model of a gyroscope mounted onto an actuated gimbal was derived and simulated. To prove the concept worked, a custom-built platform showed it is possible for a balancing robot to stay upright with zero traction under the wheels.
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Hellman, Hanna, and Henrik Sunnerman. "Two-Wheeled Self-Balancing Robot : Design and control based on the concept of an inverted pendulum." Thesis, KTH, Maskinkonstruktion (Inst.), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-184490.
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In the last decade, the open source community has expanded to make it possible for people to build complex products at home. [13] In this thesis a two-wheeled self-balancing robot has been designed. These types of robots can be based on the physical problem of an inverted pendulum [12]. The system in itself requires active control in order to be stable. Using open source microcontroller Arduino Uno and reliable angular and positional data the system can be made stable by implementing a controller. A modern and efficient controller is the LQR - Linear Quadratic Regulator [12]. Being a state space feedback controller the model has to be a good representation of reality since the output signal depends on the model. In this thesis, the validation process was performed using a PID-regulator. The results showed that the model is not yet reliable. The reasons for this are discussed and recommendations for future development are listed.<br>Öppen källkod har under senaste årtiondet möjliggjort för intresserade att bygga avancerade produkter hemma [13]. I denna rapport avhandlas konstruktion och reglering av en tvåhjulig självbalanserande robot. Denna kategori av robotar kan baseras på problemet för en inverterad pendel[12]. Systemet är i sig självt instabilt och kräver reglering för att balansera. Genom mikrokontrollern Arduino Uno och pålitlig vinkel- och positionsdata kan systemet regleras för att uppnå stabilitet. En modern och effektiv kontroller är LQR - Linear Quadratic Regulator [12]. Eftersom denna bygger på tillståndsåterkoppling måste modellen av systemet vara pålitlig då utsignalen baserar sig på modellen. I denna rapport har valideringsprocessen genomförts genom implementation av en PID-kontroller. Resultaten visade att modellen ännu inte är pålitliig. Anledningen till detta diskuteras och rekommendationer för fortsatt utveckling listas.
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Wilson, Bradford Asin. "Mechanical Design of the Legs for OLL-E, a Fully Self-Balancing, Lower-Body Exoskeleton." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/93574.
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Exoskeletons show great promise in aiding people in a wide range of applications. One such application is medical rehabilitation and assistance of those with spinal cord injuries. Exoskeletons have the potential to offer several benefits over wheelchairs, including a reduction in the risk of upper-body injuries associated with extended wheelchair use. To fully mitigate this risk of injury, exoskeletons will need to be fully self-balancing, able to move and stand without crutches or other walking aid. To accomplish this, the Orthotic Lower-body Locomotion Exoskeleton (OLL-E) will actuate 12 Degrees of Freedom, six in each leg, using custom design linear series elastic actuators. The placement of these actuators relative to each joint axis, and the geometry of the linkage connecting them, were critical to ensuring each joint was capable of producing the required outputs for self-balancing locomotion. In pursuit of this goal, a general model was developed, relating the actuator's position and linkage geometry to the actual joint output over its range of motion. This model was then adapted for each joint in the legs and compared against the required outputs for humans and robots moving through a variety of gaits. This process allowed for the best placement of the actuator and linkages within the design constraints of the exoskeleton. The structure of the exoskeleton was then designed to maintain the desired geometry while meeting several other design requirements such as weight, adjustability, and range of motion. Adjustability was a key factor for ensuring the comfortable use of the exoskeleton and to minimize risk of injury by aligning the exoskeleton joint axes as close as possible to the wearer's joints. The legs of OLL-E can accommodate users between 1.60 m and 2.03 m in height while locating the exoskeleton joint axes within 2 mm of the user's joints. After detailed design was completed, analysis showed that the legs met all long-term goals of the exoskeleton project.<br>Master of Science<br>Exoskeletons show great promise in aiding people in a wide range of applications. One such application is medical rehabilitation and assistance of those with spinal cord injuries. Exoskeletons have the potential to offer several benefits over wheelchairs, including a reduction in the risk of upper-body injuries associated with extended wheelchair use. To best reduce this risk of injury, exoskeletons will need to be fully self-balancing, able to move and stand without crutches or relying on any other outside structure to stay upright. To accomplish this, the Orthotic Lower-body Locomotion Exoskeleton (OLL-E) will use a set of custom designed motors to apply power and control to 12 joints, six in each leg. Where these motors were placed, and how they connect to the joints they control, were critical to ensuring the exoskeleton was able to self-balance, walk, and climb stairs. To find the correct position, a set of equations was developed to determine how different positions changed each joints’ speed, strength, and range of motion. These equations were then put into a piece of custom software that could quickly evaluate different joint layouts and compare the capabilities against measurements from people and robots walking, climbing stairs, and standing up out of a chair. This process allowed for the best placement of the motors and joints while still keeping the exoskeleton relatively compact. The rest of the exoskeleton was then designed to connect these joints together, while meeting several other design requirements such as weight, adjustability, and range of motion. Adjustability was very important for ensuring the comfortable use of the exoskeleton and to minimize risk of injury by ensuring that the exoskeleton legs closely matched the movements of the person inside. The legs of OLL-E can accommodate users between 1.60 m and 2.03 m in increments of 7 mm. After detailed design was completed, additional analyses were performed to check the strength of the structure and ensure it met other long-term goals of the project.
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Kendrick, John Thomas. "Design of High-Performance, Dual-Motor Liquid-Cooled, Linear Series Elastic Actuators for a Self-Balancing Exoskeleton." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/83236.
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As a valuable asset in human augmentation and medical rehabilitation, exoskeletons have become a major area for research and development. They have shown themselves to be effective tools for training and rehabilitation of individuals suffering from limited mobility. However, most exoskeletons are not capable of balancing without the assistance of crutches from the user. Leveraging technology and techniques developed for force controlled humanoid robots, a project was undertaken to develop a fully self-balancing, compliant lower-body robotic exoskeleton. Due to their many beneficial features, series elastic actuators were utilized to power the joints on the exoskeleton. This thesis details the development of four linear series elastic actuators (LSEA) as part of this project. All 12-degrees of freedom will be powered by one of these four LSEA's. Actuator requirements were developed by examining human gait data and three robot-walking simulations. These four walking scenarios were synthesized into one set of power requirements for actuator development. Using these requirements, analytical models were developed to perform component trade studies and predict the performance of the actuator. These actuators utilize high-efficacy components, parallel electric motors, and liquid cooling to attain high power-to-weight ratios, while maintaining a small lightweight design. These analyses and trade studies have resulted in the design of a dual-motor liquid-cooled actuator capable of producing a peak force 8500N with a maximum travel speed of 0.267m/s, and three different single-motor actuators capable of producing forces up to 2450N continuously, with a maximum travel speeds up to 0.767m/s.<br>Master of Science
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Jiruška, Jiří. "Návrh a řízení samobalancujícího robotu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2016. http://www.nusl.cz/ntk/nusl-240791.
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This thesis deals with complete design and manufacturing of autonomous two wheeled self-balancing robot. The goal of this thesis is to maintain the robot in up-right position and to follow black line using camera. The robot is controlled using Raspberry Pi and driven by DC motors. This thesis includes the design and implementation of hardware and software parts. Subsequently there was created the dynamic model in Matlab/Simulink. Based on this model, the LQR and PID controller was designed.
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Wang, Dian-Kai, and 王殿凱. "A Self-Balancing Robot Implemented with PID Control." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/46697375183200117912.
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碩士<br>義守大學<br>電子工程學系碩士班<br>98<br>A self-balancing robot controller is a time-variant system. The center of gravity will be changed when the robot is moving. The method that controls the center of gravity is the key point of this research. We have completed the robotic controller simulation with robot self-balancing, balancing from the fallen state and obstacle avoiding by using Lego Mindstorms NXT Kit. In a preliminary experiment, The parameters of PID controller were generated by using the measurements from gyro sensor and degree-encoders of motors. The robot is able to achieve self-balancing with the control algorithm. Next, the possibility of the robot to get up from fallen state and achieve self-balancing is experimented. By analyzing the status of the robot from the fallen state to the balance state, we have made the corresponding plans of the robot from one state to other state. The third experiment of our robot is obstacle avoiding. We made a module of ultrasonic sensors to solve the problem with PID control.
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yan, Guo Jhu, and 郭主彥. "Adaptive Cruise Control of a self-Balancing Robot." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/s82rnd.
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碩士<br>國立臺北科技大學<br>機電整合研究所<br>104<br>In this dissertation, a self-balancing two-wheeled robot was built by using LEGO bricks and LEGO Mindstorm NXT to prooved the theory of a self-balancing two-wheeled robot. After self balacing a cam was collocated to the robot to add efficiency to adaptive cruise control. Because the self-balancing two-wheeled robot itself uses a time-variant system, it is likely to lose stability when the balancing system and adoptive cruise control are require to execute at the same time, they interfer with each other easily. Therefore, the main difficulty to over come is “How to keep the balance when carrying on adoptive cruise control”, the second is how to track the object correctly. To this end, we used PID control motor to output the power, this will allow the robot to keep balance itself. Then, three adaptive cruise control tactics are used: (1)PID controller (2)fuzzy contrller (3) fuzzy sliding controller. We apply all above in the self-balancing two-wheeled robot to evaluate its control function, this will enable the robot to keep balance when it is moving and by using the cam it can detect the object and estimate it correct position, all these enable the robot to keep self balance and track object at the same time.
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Miao, Shi-Heng, and 苗士恒. "Design and Implementation of Self-Balancing Two-Wheeled Robot." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/62803468035114328063.
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碩士<br>淡江大學<br>電機工程學系碩士班<br>98<br>In this thesis, a two-input-one-output fuzzy controller is design and implemented based on the SOPC (System on a Programmable Chip) technique to let the implemented two-wheeled robot can balance by itself and let the robot reinstate the balancing state quickly when some output perturbation is produced. The chassis of robot has two wheels which are controlled by two DC motors and the control board of robot is a Nios II development board which processes all the signal and motor control. In the signal process, an one-axle gyro and a three-axle accelerometer are used to measure the tilt angle and angle velocity of robot. Furthermore, the Kalman filter is used to improve the measurement errors caused by the gyro and accelerometer so that a correct tilt angle can be obtained. The tilt angle measured by the Kalman filter and the angle velocity measured by the gyro are used to be two inputs of fuzzy controller, and the motor speed is the output of fuzzy controller. The PWM signal based on the SOPC technique is realized to control two DC motors. From some experiment results, we can see that the implemented fuzzy controller actually let the two-wheeled robot balance by itself.
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Chang, Yu-Yang, and 張宇揚. "Development of a two-wheeled self-balancing jumping robot." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/v6muzb.
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碩士<br>國立臺灣大學<br>機械工程學研究所<br>105<br>This thesis presents the development and characterization of a two-wheeled self-balancing jumping robot, which features advantages such as small footprint and zero turning radius. The two-wheeled self-balancing robot, which is integrated with a jumping mechanism, is capable of leaping over obstacles and exhibits excellent maneuverability.
The proposed robot consists of two mechanical structures: the jumping mechanism and the balancing-translation system. The jumping mechanism mainly consists of a cylindrical cam, a spring, and a latch. As a DC motor drives the cam, the spring is compressed and stores elastic energy. As the spring is released, the stored elastic energy is converted into kinetic energy which makes the robot jump upward impulsively. The balancing-translation system consists of an inertial measurement unit (IMU) and two DC motors with encoders. To keep the robot balanced, the controller estimates the output of the motors with LQR method by applying the attitude data measured by the sensors. Translational motions of the robot are achieved by changing the target angle which makes the robot move to keep balanced.
In order to design a proper mechanism which can accomplish the capabilities of self-balancing and jumping, analytical models of jumping mechanism and self-balancing control are derived. In addition, the dynamic system is also modeled for the controller design. In this thesis, the performance of self-balancing motions, translational motions, and jumping features are measured and discussed. The proposed self-balancing jumping robot possesses the abilities to overcome obstacles and travel through rough terrains.
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Kuo, Lung-Chun, and 郭瓏俊. "Self-Balancing and Motion Control of a Ball-Riding Robot." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/80641603674015513117.
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碩士<br>國立中興大學<br>電機工程學系所<br>100<br>This thesis presents methodologies and techniques for linear quadratic regulation (LQR) and backstepping sliding-mode motion control of a ball-riding robot driven by three omnidirectional wheels, in order to accomplish station keeping, position control and trajectory tracking. In comparison with the previous ball-riding robot, this thesis pays significant efforts on constructing a new driving mechanism, sensing and driving circuits, and establishing a dead-reckoning method and decoupling dynamic models for control purposes. Based on the linearized models of the robot, two LQR controllers are synthesized to achieve station keeping and point stabilization. To achieve time-varying trajectory tracking, the nonlinear models of the robot are employed to synthesize two backstepping sliding-mode controllers so as to achieve station keeping, point stabilization and trajectory tracking. The performance and effectiveness of two types of proposed controllers are exemplified by conducting several computer simulations on station keeping, point stabilization and trajectory tracking. Through experimental results, both proposed controllers together with the built ball-riding robot are shown capable of achieving station keeping and point stabilization.
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Ju, Shiang-Yun, and 朱祥雲. "Intelligent Motion Control of a Self–Balancing Two-Wheeled Mobile Robot." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/06593456317232688977.
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碩士<br>國立中興大學<br>電機工程學系所<br>98<br>This thesis presents techniques for intelligent motion control of a two-wheeled self-balancing mobile robot. Based on the dynamic mathematical modeling with exact parameters, two backstepping sliding-mode controllers are designed to achieve desired speed tracking and yaw rate control, in order to accomplish out trajectory tracking and stabilization. In the presence of mass and parameter variations, two intelligent motion controllers using fuzzy basis function networks (FBFN) are proposed to achieve trajectory tracking and stabilization. Simulations and experimental results indicate that the proposed motion controllers are capable of providing satisfactory control performance for trajectory tracking and stabilization.
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Kao, Shao-Chuan, and 高劭銓. "Design of Control System for a Two-Wheeled Self-Balancing Mobile Robot." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/27917627776151408156.
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碩士<br>國立勤益科技大學<br>電子工程系<br>99<br>The objective of this thesis is to design and implement a two-wheeled self-balancing mobile robot. The entire system that is an embedded system used ATmega16 CPU as the control center. The inertial sensors, signal acquisition processing and motor control were integrated into the proposed system based on the PID control theory. In the control process, the self-balancing mobile system measured the angular velocity, tilt angle and acceleration of the robot platform using gyro sensor and accelerometers. In addition, the motor encoder was used to measure two motor rotation angle and angular velocity. According to the platform information received from the gyro sensor, accelerometers and motor encoder, the proposed system used the PID control for the control center calculation. Then, the output PWM signal is to control the rotation torque and speed of motor. The experimental results confirm that the proposed approach can achieve two-wheeled mobile robot in the balanced status.
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Wang, Tzu-Chu, and 王梓竹. "Intelligent Adaptive Motion Control and Path Planning for a Self-Balancing Two-Wheeled Mobile Robot." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/70618779847283567095.
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碩士<br>國立中興大學<br>電機工程學系所<br>99<br>This thesis presents techniques for intelligent adaptive motion control and path planning of a two-wheeled self-balancing mobile robot. First, based on the dynamic mathematical model whose system functions can be decomposed into the nominal and perturbed terms, an intelligent motion controller augmented with fuzzy basis function networks is designed to achieve trajectory tracking control; this controller is composed of two control modules: posture and speed tracking, and yaw rate control. To find optimal and collision-free paths for the robot, this thesis also presents a global path planning method using the modified particle swarm optimization (MPSO) method, and then establishes a local path planning scheme using the elastic band technology. Several simulations are conducted to illustrate the feasibility and effectiveness of the proposed intelligent adaptive trajectory tracking method, PSO-based global path planning method and elastic-band-based local path planning scheme. Furthermore, some experimental results on for trajectory tracking are performed to show that the proposed intelligent motion controller is capable of giving satisfactory trajectory tracking control performance.
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Wang, Shih-Hung, and 王世泓. "Nonlinear Motion Control and Human-Aware Navigation of a Two-Wheeled Self–Balancing Mobile Robot." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/93187428635304088680.
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碩士<br>國立中興大學<br>電機工程學系所<br>97<br>This thesis presents techniques for motion control and human-aware navigation of a two-wheeled self-balancing mobile robot. Based on the nonlinear mathematical modeling, a motion commands generator and two sliding-mode controllers are designed to achieve speed tracking, yaw rate control and desired trajectory tracking. The human-aware navigation combines an obstacle-avoidance method and skin color detection, in order to provide desired socially acceptable path between humans and the robot. Simulations and experimental results indicate that the proposed motion controllers and human-aware navigation approach are capable of providing appropriate control actions to satisfactorily achieve path tracking, obstacle avoidance and mission execution.
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Che-YuLin and 林哲宇. "Realization of One-Dimensional Cube Robot Capable of Bounce and Self-balancing based on Linear Quadratic Regulator Control." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/5se3ba.
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Lin, Che-Ying, and 林哲英. "Fuzzy Reasoning Inference Associated with Genetic Algorithm Applied to a Two-Wheeled Self-Balancing Robot of LEGO Mindstorms NXT." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/76968659678982420196.
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碩士<br>臺北市立大學<br>資訊科學系<br>103<br>In this thesis, we focus on a fuzzy knowledge-based reasoning control with genetic algorithm (GA) for a LEGO two-wheeled self-balancing robot. To achieve the control objectives with the satisfied states’ responses, a GA is involved to search feasible solution sets of the state feedback gain. Based on the dynamic model provided by LEGO Mindstorms NXT, performance indices of systems’ states can be characterized as rise time (RS), overshoot (OS), and integral of absolute error (IAE). Thus, a GA with a fitness function embracing the three performance indices is thus proposed for searching a set of well response parameters. Furthermore, we employ fuzzy inference reasoning to blend multiple states’ conditions. For demonstration, the proposed approach was compared with some existing works.
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Lian, Meng-Jhe, and 連孟哲. "Obstacle Avoidance Control of Two-wheeled Self-balancing Autonomous Robots." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/9w6uk7.
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碩士<br>國立臺灣師範大學<br>工業教育學系<br>105<br>The main goal of the thesis is the design of navigation and obstacle avoidance control of a two-wheeled self-balancing autonomous robot. The body structure of the two-wheeled self-balancing autonomous robot includes motors and drivers, balancing sensor device, and obstacle avoidance and navigation device. The motor control device consists of an 8-bit microcontroller and a driver circuit. The balancing sensor device measures the inclination angle of the autonomous robot by the gyroscope and the accelerometer. The obstacle avoidance and navigation device uses ultrasonic sensors and electronic compass to measure the distance and the movement of obstacles. According to sensor devices data, the microcontroller utilizes PID controller and the fuzzy controller to achieve self-balance control, obstacle avoidance and navigation. Finally, some experimental results are given to verify the performance of the overall system.
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Lee, Kuan-Tung, and 李冠東. "Design and Implementation of Object Following Control of Two-Wheeld Self-Balancing Robots." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/96531962083248748496.
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碩士<br>國立臺灣師範大學<br>電機工程學系<br>104<br>The main goal of the thesis is the design and practical investigation of object following control of a two-wheeled self-balancing robot. The body structure of the two-wheeled self-balancing mobile robot includes the motors and drivers, sensor equipment and controllers. The sensor equipment includes a three-axis accelerometer, a gyroscope and a laser rangefinder. Because the two-wheeled self-balancing mobile robot possesses the highly non-linear and time-varying characteristics, the proportional–integral–derivative controller (PID controller) and fuzzy controller are used such that the robot achieves the object following control. Finally, some simulation and experimental results are given to verify the performance of the overall system.
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Fan, Huan-Hau, and 范元豪. "Motion Control and Planned Navigation of a Two-wheeled Self–balancing Mobile Platform for Human Symbiotic Robots." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/37141143430593707151.
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碩士<br>國立中興大學<br>電機工程學系所<br>96<br>This paper presents techniques for motion control and planned navigation of a self-balancing two-wheeled platform for autonomous service robots. Based on the linearized mathematical modeling, a kinematical trajectory tracker and two adaptive controllers are designed to achieve speed tracking and yaw rate control. Planned navigation architecture, combining a human-aware trajectory generator and an obstacle-avoidance method, is used to provide desired safe trajectories between humans and the robot. Simulations and experimental results indicate that the proposed motion controller and planned navigation control architecture are capable of providing appropriate control actions to satisfactorily achieve trajectory tracking, obstacle-avoidance and task execution.