The manipulator robot on the humanoid robot has functioned as an arm to grasp objects. The end-effector position of the robot is must first be known to perform the grasping task. Therefore, using the kinematics solution to find the robot end-effector position in the Cartesian space. This research paper presents the inverse kinematics of the 7-DOF T-FLoW humanoid robot manipulator using the Improved Damped Least Squares method with joint limits to avoid mechanical limitations. Forward Kinematics with the Homogeneous Transformation Matrix is used in the solution to find the current position of the end-effector in the Cartesian space. This research using the DLS method because it can avoid kinematic singularities and performs better than pseudoinverse based formulations. The experiment results show that the improved solution is more robust in performing joint limitation with a success rate of 100% and generating more natural motion than the original DLS.

Autonomous navigation is one of the important functions of the Healthcare Robot to produce obstacle-free movements in the social environment inhabited by humans. In carrying out its duties, the robot will do a lot of navigation from the origin to the destination. Healthcare Robot uses a Laser Range Finder to detect objects around the robot. The results of detection are distance and angle data from the object. Then, the data is used as input for the Fuzzy Inference System (FIS) process to produce an appropriate gain value to control static and dynamic force of the Social Force Model (SFM). The parameters of the SFM influence the robot's response to the detected object. To obtain the optimal gain value, the FIS is used to change the parameters adaptively. Adaptive parameters are used to prevent the robot from making unexpected navigational behavior that may be dangerous, threatening to others, and potentially self-destructive. From the tests carried out in two conditions, the robot successfully navigated from its initial position to the goal and was able to respond to objects around it with the percentage of success in all scenes was 79.9%.

Robots are a tool that is widely developed today, such as Humanoid, Animal, and others. In this study we discussed about animal robots. One such type of robot is Quadruped Robot. The problem that often arises in quadruped robots is that when performing stunts to be able to walk up or climb a ladder, the robot will not be able to walk with the posture adjusting the slope in the arena. This is due to the effect of earth's gravitational force that results in robots always being attracted to earth. This results in the robot's body losing balance and can accelerate damage to the servo motor due to the robot's unbalanced load. With this problem, this paper makes the control system with Fuzzy Logic place the load position in the middle of the COG (center of gravity) to balance the robot on the trajectory. The balance of the robot uses the IMU (Inertia Measurement Unit) position sensor reference with the reference derived from the angle slope (Yaw, Pitch and Roll) which is processed to adjust changes in the x, y and z axes, so that the robot can adapt to the trajectory of the stairs.

A robot guide is a robot that is used to guide users from a place of origin to their destination. During carrying out the guiding task, the robot must ensure that the user always follows wherever the direction is headed by the robot until it reaches the destination location. To get this certainty, one of the things that must be considered is the direction the user must walk in the direction of the robot's movement. In this paper, we built a system to monitor user awareness levels to coordinate with robots. We use RGB-D data from the Kinect sensor to detect target partners, their position, and orientation. The level of awareness is calculated using the Social Force Model (SFM) based on the target partner's position and body orientation parameters. This level of awareness will be used by the robot to evaluate the appropriate actions according to the target partner's activities. Based on the results of experiments, the level of awareness of target partners can be calculated and transformed in the form of attractive or repulsive forces towards robots.

In general, a socially-aware mobile robot must have an ability to safely navigate among human environment. To address with this competency, the mobile robots must be able to detect the existence of humans around. This paper proposes the use of Fast Fourier Transform (FFT) to analyze shape-models of human legs that is obtained from Laser Range Finder (LRF) scanning results. A 240° of LRF was used to capture and visualize the environment in one dimensional plane. The plane is then converted into one dimensional signal that consists of 1,024 data points. These data points represented the distance of all measured points. A specific set of points formed the pattern of human legs only is then resized into 32 data. This resized-data is transformed into frequency by using FFT. The result of FFT is then fed into Support Vector Machine (SVM) to be classified into two classes, they are human or not human. Based on the experimental results, our proposed method shows a promising result in order to detect human based on one dimensional feature of his legs by achieving more than 80% of accuracy.

The following topics are dealt with: mobile robots; Internet; learning (artificial intelligence); object detection; cameras; position control; image segmentation; computer aided instruction; feature extraction; wireless sensor networks.

T-FLoW (Teen FLoW) is one of the teen size humanoid robots developed by ER2C (EEPIS Robotics Research Center) laboratory. There are various problems that occur when the robot performs dynamic locomotion, one of them is the overloading received on every actuator thus causing the asynchronous locomotion of the robot. In this paper, the goal to be achieved is making a vertical jumping mechanism of the robot to become more synchronized. Therefore, multivariable control will be used as a method to distribute overload for each actuator on the same joint so that actuator can be more synchronized. Finally, multivariable control has a positive effect in which the success rate of the vertical jumping mechanism is about 80%, and the robot managed to hover on the air for about 7-9 ms.

Research on the control of movement omnidirectional on mobile robots have been much done. On the problems there are in the Asia-Pacific Robot Contest (ABU Robocon) 2014, about the trajectory of the line on a robot that cannot be used as a reference point for the trajectory of the movement from the robot. If using the line as a reference and no field the entire area cannot be mapped, so that only part that there is a line of course that can be passed by a robot. Some method of tracking the path that is used will form new path when the robot out of the set so that the movement of the robot not appropriate. Many researchers has done research on a method of tracking the path on omnidirectional use to maintain control of robots to maintain in order to stay on track. Pure pursuit and bicycle path planning are other methods used path tracking. This paper the researchers did research on comparing the two method, there are pure pursuit path tracking and bicylce path planning. From both of these methods, methods bicycle path planning RMSE values to track the movement of the robot is smaller than the pure pursuit method. With the smallest RMSE value of the bicycle path planning methods at 2.59 cm and pure pursuit method 3.10 cm, while the largest of the methods bicycle path planning methods 7.9 cm and 7.57 cm pure pursuit.