“…Roller tengah dapat digerakan oleh sebuah motor penggerak dengan arah putaran sejajar arah sumbu-y bidang kartesian. Sedangkan, roller pinggir dapat digerakan ketika roda omni mendapatkan kecepatan induksi [9]. Kecepatan induksi berasal dari luar roda tersebut dan mampu menggerakan roda omni ke arah sumbu-x.…”
Section: Metode Penelitianunclassified
“…Berdasarkan [9], persamaan forward kinematics yang dibentuk berdasarkan gerak rotasi dan translasi ini dapat dijelaskan sebagai berikut.…”
Section: Gambar 2 Ilustrasi Vektor Gerakan Roda Omnidireksionalunclassified
Gerak robot omnidireksional dibangkitkan dengan cara mengatur kecepatan putaran pada tiga roda omnidireksional yang terpasang pada poros penggerak agar mampu bergerak ke segala arah tanpa perlu reorientasi. Pengaturan kecepatan ini membutuhkan metode dan strategi pengendalian yang tepat. Ketepatan ini berhubungan erat dengan kemampuan robot untuk tetap kokoh ketika berhadapan dengan gangguan. Penelitian ini bertujuan untuk membuat sebuah pengendali gerak robot omnidireksional menggunakan pengendali PID. Data hasil penelitian menunjukan bahwa manuver gerak robot ini dipengaruhi oleh pengaturan arah dan besar nilai kecepatan ketiga motor penggerak yang terpasang pada robot. Berdasarkan set point sebesar 100 rpm dengan perintah arah gerak maju, catatan kriteria tanggapan peralihannya adalah waktu naik pada detik ke 2.8, waktu puncak pada detik ke 4 dan waktu keadaan mantap detik ke 4. Kesalahan keadaan mantap cenderung mendekati nol, dengan nilai sebesar 0.71 rpm, tanpa adanya lewatan dan variasi puncak-puncak tanggapan. Tanggapan ini diperoleh dengan pengaturan parameter konstanta pengendali PID untuk motor kiri dan kanan masing-masing adalah [0.000999747; -0.00002725;-50] dan [-0.000554; -0.00585;0].
“…Roller tengah dapat digerakan oleh sebuah motor penggerak dengan arah putaran sejajar arah sumbu-y bidang kartesian. Sedangkan, roller pinggir dapat digerakan ketika roda omni mendapatkan kecepatan induksi [9]. Kecepatan induksi berasal dari luar roda tersebut dan mampu menggerakan roda omni ke arah sumbu-x.…”
Section: Metode Penelitianunclassified
“…Berdasarkan [9], persamaan forward kinematics yang dibentuk berdasarkan gerak rotasi dan translasi ini dapat dijelaskan sebagai berikut.…”
Section: Gambar 2 Ilustrasi Vektor Gerakan Roda Omnidireksionalunclassified
Gerak robot omnidireksional dibangkitkan dengan cara mengatur kecepatan putaran pada tiga roda omnidireksional yang terpasang pada poros penggerak agar mampu bergerak ke segala arah tanpa perlu reorientasi. Pengaturan kecepatan ini membutuhkan metode dan strategi pengendalian yang tepat. Ketepatan ini berhubungan erat dengan kemampuan robot untuk tetap kokoh ketika berhadapan dengan gangguan. Penelitian ini bertujuan untuk membuat sebuah pengendali gerak robot omnidireksional menggunakan pengendali PID. Data hasil penelitian menunjukan bahwa manuver gerak robot ini dipengaruhi oleh pengaturan arah dan besar nilai kecepatan ketiga motor penggerak yang terpasang pada robot. Berdasarkan set point sebesar 100 rpm dengan perintah arah gerak maju, catatan kriteria tanggapan peralihannya adalah waktu naik pada detik ke 2.8, waktu puncak pada detik ke 4 dan waktu keadaan mantap detik ke 4. Kesalahan keadaan mantap cenderung mendekati nol, dengan nilai sebesar 0.71 rpm, tanpa adanya lewatan dan variasi puncak-puncak tanggapan. Tanggapan ini diperoleh dengan pengaturan parameter konstanta pengendali PID untuk motor kiri dan kanan masing-masing adalah [0.000999747; -0.00002725;-50] dan [-0.000554; -0.00585;0].
“…l 1 , l 2 , l 3 is the horizontal distance from the geometric center of the car body to the center of the three wheels. R is the radius of the wheel [32].…”
Due to their high mobility, mobile robots (MR) are widely used in intelligent manufacturing. Due to the perfect symmetry of the MR of the three-wheeled moving chassis, it can move quickly in a crowded and complex factory environment. Because it is powered by a lithium battery, in order to improve its energy efficiency, we need to ensure that its power consumption is reduced as much as possible in order to avoid frequent battery replacement. The power consumption of MRs has also become an important research focus for researchers. Therefore, a power consumption modeling of the omnidirectional mobility of the three-wheeled omnidirectional mobile robot (TOMR) is proposed in this paper. When TOMR advances heading at different angles, the speed of each wheel changes dramatically. So, the power consumption of robots will also be greatly changed. In this paper, the energy and power consumption of the robot heading in different directions is analyzed and modeled by formulas. This research can be valuable for path planning and control design. Omnidirectional wheel (a) (b) Figure 1. Three-wheeled omnidirectional mobile robot (TOMR). (a) Schematic of TOMR and a (b) schematic diagram of robot architecture.
“…In the field of manufacturing, transportation platforms are widely used in all aspects of producing products. In comparison with normal wheeled vehicles, although omnidirectional wheel movements are more complicated, they are able to travel through very narrow and complicated spaces and their movements are not easily constrained by the terrain surface or obstacles and are thus better choices in many industrial applications (Yamada et al 2017;Hacene and Mendil 2019;Qian et al 2017).…”
Omnidirectional mobile platform is essential due to its excellent mobility and versatility. With the development of the manufacturing industry, how to transport oversized or overweight goods has become a new problem. Compared with manufacturing omnidirectional mobile platforms with different specifications, it is more cost-effective and flexible to coordinate two non-physically connected omnidirectional platforms to transport overweight and oversized cargo. The roughness of the actual deployment environment and the mechanical deflection between the two vehicles have a significant impact on the normal operation of the system. This paper combines mechanical wheels, image processing algorithms and collaboration algorithms to create a novel and practical split-type omnidirectional mobile platform based on image deviation prediction for transporting oversized or overweighted goods. The proposed system collects raw measurements from a distance sensor and an image sensor, transmits them to a central processing unit through a wireless communication module and calculates and predicts the relative deflection between the two vehicles based on our derived mathematical model. This information is then fed to a Kalman filter and PID control algorithm to coordinate the two vehicles. The effectiveness and performance of our system have been thoroughly tested, which has already been applied in a bullet train production line.
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