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.

abstract: Bicycle stabilization has become a popular topic because of its complex dynamic behavior and the large body of bicycle modeling research. Riding a bicycle requires accurately performing several tasks, such as balancing and navigation which may be difficult for disabled people. Their problems could be partially reduced by providing steering assistance. For stabilization of these highly maneuverable and efficient machines, many control techniques have been applied – achieving interesting results, but with some limitations which includes strict environmental requirements. This thesis expands on the work of Randlov and Alstrom, using reinforcement learning for bicycle self-stabilization with robotic steering. This thesis applies the deep deterministic policy gradient algorithm, which can handle continuous action spaces which is not possible for Q-learning technique. The research involved algorithm training on virtual environments followed by simulations to assess its results. Furthermore, hardware testing was also conducted on Arizona State University’s RISE lab Smart bicycle platform for testing its self-balancing performance. Detailed analysis of the bicycle trial runs are presented. Validation of testing was done by plotting the real-time states and actions collected during the outdoor testing which included the roll angle of bicycle. Further improvements in regard to model training and hardware testing are also presented. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2020

This rapport deals with the construction of a self-balancing scooter. A self-balancing scooter is a two-wheel vehicle where the velocity is controlled by the tilt of the driver. When the driver leans forward and backward, the vehicle is running forward and backwards. The main task was to determine if the Arduino microcontroller could be used for the control system. An iron frame, control circuit and a tilt able handlebar were constructed. Two recycled permobil DC-motor were mounted onto the iron frame. An accelerometer and a gyrometer were obtaining the tilt of the handlebar and the scooter. The system was using locked Anti-phase drive and a PI-regulator to control the motors. The self-balancing scooter prototype worked well and was able to balance without any external help. The driver was able to control the speed by tilting forward or backward and was able to choose the direction by the tilt of the handlebar. The balance was affected negative by the backlashes from the gear and too weak H-bridges. If the project were made again, two three-phase hub motors with higher ratings would replace the DC-motors. Gears could be excluded and the backlashes are removed.

Tato práce se zabývá návrhem nového řídícího systému, odolného proti chybám, pro nestabilní samo-balancující dvoukolové vozidlo typu Segway. Původní systém vozidla je podroben analýze rizikovosti jeho součástí a na základě výsledků jsou navržena opatření pro zvýšení jeho bezpečnosti. Je navržena nová topologie řídícího systému obsahující dvě samostatné řídící jednotky, redundantní senzoriku a voter. Pro řídící jednotky byl vyvinut software obsahující bezpečnostní algoritmy a mechanismy přepínání kontrolních výstupů. V práci jsou také představeny dva matematické modely vozidla různé složitosti, které jsou následně využity při HIL testování nově navrženého systému. Celý návrh byl proveden s využitím nástrojů pro Rapid Control Prototyping.

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. / 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.

Táto práca sa zaoberá vývojom, testovaním a implementáciou adaptívneho riadiaceho systému pre dvojkolesové samobalancujúce vozidlo. Adaptácia parametrov vozidla sa uskutoční na základe parametrov vodiča. Parametre sústavy sa nemerajú priamo, ale sú odhadované na základe priebehu stavových premenných a odozvy sústavy. Medzi odhadované parametre patrí hmotnosť a poloha ťažiska vodiča. Cieľom práce je zabezpečiť adaptáciu jazdných vlastností vozidla k rôznym vodičom s rôznou hmotnosťou, kvôli zlepšeniu stability vozidla. Táto práca je pokračovaním predchádzajúcich projektov z roku 2011 a 2015.

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.

This report presents the construction of a two-wheeled self balancing robot with the ability to handle an uneven load. Two-wheeled self-balancing robots have proven to be a potential solution to the problem of efficient warehouse management, thanks to their ability to navigate tight spaces quickly and efficiently while balancing their load. The research questions defined include the ability to develop an algorithm to dynamically adjust the robot’s tilt angle, how an uneven load affects the robot’s stability, and whether a PID controller is sufficient in this context. The project was limited to constructing a prototype that could balance with an external load, with a budget of 1,000 Swedish kronor and a four-month timeframe. By testing and evaluating different control algorithms, the robot’s performance was presented in terms of stability and efficiency. The implementation of PID control was successful, and the robot was able to balance as a result. However, the goal of handling an uneven load was not met without the implementation of an additional algorithm to dynamically adjust the robot’s tilt angle. With these two control techniques, the robot was able to balance with and without an added load with good stability. To evaluate performance, tests were performed with the load placed centered and off-centered on the robot’s top plate. The results of the tests showed that the robot was able to dynamically adjust its tilt angle to balance with added weight without affecting stability. / Denna rapport presenterar konstruktionen av en tvåhjulig självbalanserande robot med förmågan att hantera snedfördelad last. Tvåhjuliga självbalanserande robotar har visat sig vara en potentiell lösning på problemet kring effektiv lagerhantering tack vare deras förmåga att hantera snäva utrymmen på ett snabbt och energieffektivt sätt samtidigt som lasten balanseras. Forskningsfrågorna som definierades inkluderar möjligheten att framställa en algoritm för att dynamiskt ställa in robotens lutningsvinkel, hur ojämn last påverkar robotens stabilitet, och om en PID-kontroller är tillräcklig i detta sammanhang. Projektet begränsades till att konstruera en prototyp som klarar av att balansera med extern last, med en budget på 1000 svenska kronor och en tidsram på fyra månader. Genom att testa och utvärdera olika kontrollalgoritmer presenterades robotens prestanda i termer av stabilitet och effektivitet. Roboten balanserade tack vare implementeringen av PID-reglering, men önskemålet om snedfördelad last uppfylldes inte och det krävdes ytterligare en algoritm för att dynamiskt reglera robotens lutningsvinkel. Med hjälp av dessa två reglertekniker kunde roboten balansera både med och utan adderad last med god stabilitet. Tester utfördes för att utvärdera prestandan när lasten var placerad både centrerat och ocentrerat på robotens topplatta. Resultaten visade att roboten kan dynamiskt anpassa lutningsvinkeln för att balansera med tillagd vikt utan att stabiliteten påverkas.

This report is a bachelor thesis in Mechatronics at KTH. The purpose of the thesis is to design a statically stable walking robot capable of forward movement. A quadrupedal robot is designed, as well as a PID control system. To easily control the legs with sufficient accuracy servo motors are used. The control system is used to generate an effective gait pattern that gives rise to the desired functionality. To achieve this the center of mass needs to be approximated, which is done through force sensitive resistors in its feet. The control systems and mathematical models used are tested with the help of a simulation in Simulink. A prototype is also built in order to test the models in practice. The results show that the robot is capable of upholding balance in the simulations, even with shifts in parameters such as the weight and the location of the center of mass. The prototype performed significantly worse, which is mainly accredited to the lack of quality among the force sensors. In future projects the use of different methods to approximate the location of the center of mass is recommended. If the use of sensors is preferred, strain gauges could be a viable alternative to the force sensitive resistors used. More expensive force sensitive resistors of a higher quality could also be an option. / Denna rapport är ett kandidatexamensarbete i Mekatronik på KTH. Syftet med rapporten är att designa en gående robot som erhåller statiskt stabilitet vid gång framåt. En fyrbent robot samt ett PID regler system designades. För att styra benen med bra noggranhet används servomotorer. Reglersystemet används för att generera en stabil bana för fötterna att följa. Detta kräver en uppskattning av robotens masscentrum som möjliggös m.h.a. tryckkänsliga motstånd i fötterna. Reglersystemet samt framtagna matematiska modeller testas med hjälp av simulering i Simulink. Sedan byggs en prototyp av roboten för att testa modellerna i verkligheten. Resultat visar att roboten kan balansera och presterar bra i simulationen, även då parametrar så som vikt och masscentrumets läge ändras. I verkligheten fungerade roboten betydligt sämre, vilket tycks vara orsakat av opålitliga kraftsensorer i fötterna. I framtida projekt föreslås användning av olika metoder för att uppskatta positionen av robotens masscentrum. Om användningen av sensorer är föredragen kan tryckkänsliga motstånd ersättas med töjningsgivare för att mäta normalkrafterna, alternativt kan tryckkänsliga motstånd av högre kvalitet användas.

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.