A deburring system using the joint of revolute robot manipulator with a tool holder was developed for deburring automation. The tool holder composed of the plunger with spring was developed for freedom of three degree operation. The tool holder was applied for compensation of position errors during trajectory tracing or deburring the workpiece of ununiform. To reduce interacting forces between the high stiffness tool at the end effecter and the workpiece during deburring operation, it was developed to operate flexibly to the direction of tangent line on the revolute axis and to the direction of axis. In this paper, using the deburring system attached at the revolute robot manipulator, deburring experiments were performed. According to the experimental results, the good performance of the proposed deburring system using the revolute robot manipulator was shown.

This paper deals with the stability of industrial robot arms with six axes and six degrees of freedom. The robot arm used was IRB120, a product of ABB company, which is used in the real industry, by using the commercial “DAFUL” which is a simulation program that can analyze the dynamic behavior. DAFUL was applied to the robot arm to control the motion by applying the load to the robot arm and then the structural analysis of the robot arm was performed during the analysis time. As a result of the analysis of the robot arm, the stress and displacement acting on the elliptic model and the acting torque and force were analyzed. Based on the analysis results, stability was checked with reference to IRB120 product catalog.

Recently, a study on reducing the weight of the robot arm, which enables a high-speed operation and enables reducing the energy consumption has been actively carried out. A lightweight robot arm is hard to control because it behaves like a flexible body rather than a rigid body. This paper proposes a controller which combines a PID controller and a fuzzy logic controller for control the position and vibration of the flexible robot arm. In order to show the effectiveness of the proposed controller, MSC.ADAMS computational model which incorporates the finite element flexible robot arm model is developed, and is used for performing simulations. Simulations are carried out with two reference inputs, and three end masses. Simulation results show that the proposed controller controls the position and vibration of the flexible robot arm adaptively without being affected by the reference input and the end mass.

This paper proposes a low-cost robotic surgery system composed of a general purpose robotic arm, an interface for daVinci surgical robot tools and a modular haptic controller utilizing smart actuators. The 7 degree of freedom (DOF) haptic controller is suspended in the air using the gravity compensation, and the 3D position and orientation of the controller endpoint is calculated from the joint readings and the forward kinematics of the haptic controller. Then the joint angles for a general purpose robotic arm is calculated using the analytic inverse kinematics so that that the tooltip reaches the target position through a small incision. Finally, the surgical tool wrist joints angles are calculated to make the tooltip correctly face the desired orientation. The suggested system is implemented and validated using the physical UR5e robotic arm.

In the agricultural field, interests in research using robots for fruit harvesting are continuously increasing. Dual arm manipulators are promising because of its abilities like task-distribution and role-sharing. To operate it efficiently, the task sequence must be planned adequately. In our previous study, a collision-free path planning method based on a genetic algorithm is proposed for dual arm manipulators doing tasks cooperatively. However, in order to simplify the complicated collision-check problem, the movement between tasks of two robots should be synchronized, and thus there is a problem that the robots must wait and resume their movement. In this paper, we propose a heuristic algorithm that can reduce the total time of the optimal solution obtained by using the previously proposed genetic algorithm. It iteratively desynchronizes the task sequence of two robots and reduces the waiting time. For evaluation, the proposed algorithm is applied to the same work as the previous study. As a result, we can obtain a faster solution having 22.57 s than that of the previous study having 24.081 s. It will be further studied to apply the proposed algorithm to the fruit harvesting.

Home robot arms require a payload of 2 kg to perform various household tasks; at the same time, they should be operated by low-capacity motors and low-cost speed reducers to ensure reasonable product cost. Furthermore, as robot arms on mobile platforms are battery-driven, their energy efficiency should be very high. To satisfy these requirements, we designed a lightweight counterbalance mechanism (CBM) based on a spring and a wire and developed a home robot arm with five degrees of freedom (DOF) based on this CBM. The CBM compensates for gravitational torques applied to the two pitch joints that are most affected by the robot’s weight. The developed counterbalance robot adopts a belt-pulley based parallelogram mechanism for 2-DOF gravity compensation. Experiments using this robot demonstrate that the CBM allows the robot to meet the above-mentioned requirements, even with low-capacity motors and speed reducers.

This work presents a design and control method for a flexible robot arm operated by a wire drive that follows human gestures. When moving the robot arm to a desired position, the necessary wire moving length is calculated and the motors are rotated accordingly to the length. A robotic arm is composed of a total of two module-formed mechanism similar to real human motion. Two wires are used as a closed loop in one module, and universal joints are attached to each disk to create up, down, left, and right movements. In order to control the motor, the anti-windup PID was applied to limit the sudden change usually caused by accumulated error in the integral control term. In addition, master/ slave communication protocol and operation program for linking 6 motors to MYO sensor and IMU sensor output were developed at the same time. This makes it possible to receive the image information of the camera attached to the robot arm and simultaneously send the control command to the robot at high speed.

Reinforcement learning has been applied to various problems in robotics. However, it was still hard to train complex robotic manipulation tasks since there is a few models which can be applicable to general tasks. Such general models require a lot of training episodes. In these reasons, deep neural networks which have shown to be good function approximators have not been actively used for robot manipulation task. Recently, some of these challenges are solved by a set of methods, such as Guided Policy Search, which guide or limit search directions while training of a deep neural network based policy model. These frameworks are already applied to a humanoid robot, PR2. However, in robotics, it is not trivial to adjust existing algorithms designed for one robot to another robot. In this paper, we present our implementation of Guided Policy Search to the robotic arms of the Baxter Research Robot. To meet the goals and needs of the project, we build on an existing implementation of Baxter Agent class for the Guided Policy Search algorithm code using the built-in Python interface. This work is expected to play an important role in popularizing robot manipulation reinforcement learning methods on cost-effective robot platforms.

Robot arms are being increasingly used in various fields with special attention given to unmanned systems. In this research, we developed a high payload dual-arm robot, in which the forearm module is replaceable to meet the assigned task, such as object handling or lifting humans in a rescue operation. With each forearm module specialized for an assigned task (e.g. safety for rescue and redundant joints for object handling task), the robot can conduct various tasks more effectively than could be done previously. In this paper, the design of the high payload dual-arm robot with replaceable forearm function is described in detail. Two forearms are developed here. Each of forearm has quite a different goal. One of the forearms is specialized for human rescue in human familiar flat aspect and compliance parts. Other is for general heavy objects, more than 30 kg, handling with high degree of freedom more than 7.

Recently, development of robot technology has been actively investigated that industrial robots are used in various other fields. However, the interface of the industrial robot is limited to the planned and manipulated path according to the target point and reaching time of the robot arm. Thus, it is not easy to create or change the various paths of the robot arm in other applications, and it is not easy to control the robot so that the robot arm passes the specific point precisely at the desired time during the course of the path. In order to overcome these limitations, this paper proposes a new-media content management platform that can manipulate 6 DOF industrial robot arm using 3D game engine. In this platform, the user can directly generate the motion of the robot arm in the UI based on the 3D game engine, and can drive the robot in real time with the generated motion. The proposed platform was verified using 3D game engine Unity3D and KUKA KR-120 robot.

In this article art performing applications of industrial dual-arm robots are introduced. It was real collaboration among robot researchers and artist. Artist designed the performance to use dual-arm robot. Robot researchers collaborated with artist by providing robotic constraints and configuring robot motion. Two art performances were configured with two industrial dual-arm robots. In both performance robots carry objects to be used as moving screens. Both performances rely on the high power and high precision of robots. In addition human-like appearance make those performances be familiar to public

Dual arm manipulators have been developed for the entertainment purpose such as humanoid type or the industrial application such as automatic assembly. Nowadays, there are some issues for applying the dual arm robot system into the various fields. Especially, robots can substitute human and perform the dangerous activity such as search and rescue in the battle field or disaster. In the paper, the dual arm manipulator which can be adapted to the rescue robot with the mobile platform was developed. The kinematic design was proposed for the rescue activity and the required specification was determined through the kinematic analysis and the dynamic analysis in the various conditions. The proposed dual arm manipulator was manufactured based on the vibration analysis result and its performance was proved by the experiment.

Peg-in-hole assembly is the most representative task for a robot to perform under contact conditions. Various strategies for accomplishing the peg-in-hole task with a robot exist, but the existing strategies are not sufficiently practical to be used for various assembly tasks in a human environment because they require additional sensors or exclusive tools. In this paper, the peg-in-hole assembly experiment is performed with anthropomorphic hand arm robot without extra sensors or devices using “intuitive peg-in-hole strategy”. From this work, the probability of applying the peg-in-hole strategy to a common assembly task is verified.

This paper introduces a dual-arm robot painter system which is capable of sketching a camera-captured image with short line segments. To express various curved edges in the image by combining line segments, we first apply edge detection algorithm to the entire image, split the edged image into small boxed pieces, and then apply Hough Transformation to each piece so that the edges inside the piece can be approximated with short line segments. To draw the picture within a reasonable time, we designed a simple dual-arm robot system and controlled both arms concurrently according to linear interpolation algorithm. From the experiments, we could verify that simple linear motions can describe various images effectively with a unique brush style.

This paper proposes a performance index for the multiple shape object handling of dual arm manipulator to determine whether a robot is good or not. When the dual‐arm manipulator grasps a fixed object and is posed, the dual‐arm manipulator should procure a space to freely control the manipulator. As a performance evaluation parameter, each joint torque from current sensor signal is utilized. From the current information, torque and energy for each joint are estimated. In this paper an performance index for an unstructured object is defined by an energy‐cost function, and stability analysis for each motion is derived by the maximum force to the object. The maximum force to the object is computed by the inertia of object and acceleration information of end‐effector. The acceleration data are derived by the double derivation of each encoder signal. Manipulability measure which implies how efficiently the dual –arm manipulator can move with the grasped object, can be represented by the intersection of the two manipulability ellipsoids for the left and right arms. Effectiveness of the proposed algorithm has been verified through the practical simulations and real experiments.

This paper proposes an optimal posture for the task-oriented movement of dual arm manipulator. A stability criterion function which consists of three kinds of feature-representative parameters has been utilized to define the optimal posture. The first parameter is the force which is applied to the object. The torque of each joint and position of arm are attained from the current sensor and encoder, respectively. From these two data, the applied force to an object is estimated using sum of vectors of the joint torques estimated from the measured current. In order to investigate the robustness of each posture, the variation of the end-effector from the encoder information has been utilized as the second parameter. And for the last parameter for the optimality, the total energy consumption has been used. The total consuming energy of each posture can be computed from the current information and the battery voltage. The proposed robot structure consists of a mobile inverted pendulum and dual manipulators. In order to define the optimal posture for the each object, external disturbances are applied to the mobile inverted pendulum robot and the first and second parameters are investigated to find the optimal posture among the pre-selected most representative postures. Finally, the proposed optimal posture has been verified by the proposed stability criterion function which consists of total force to the object, the fluctuation of the end-effector position, and total energy consumption. The effectiveness of the proposed algorithms has been verified and demonstrated through the practical simulations and real experiments.

Control and trajectory generation of a 7 DOF anthropomorphic robot arm suffer from computational complexity and singularity problem because of numerical inverse kinematics. To deal with such problems, analytical methods for a redundant robot arm have been researched to enhance the performance of inverse kinematics. In this research, we propose an analytical inverse kinematics algorithm for a 7 DOF anthropomorphic robot arm. Using this algorithm, it is possible to generate a trajectory passing through the singular points and intuitively move the elbow without regard to the end-effector pose. Performance of the proposed algorithm was verified by various simulations. It is shown that the trajectory planning using this algorithm provides correct results near the singular points and can utilize redundancy intuitively.

This paper introduces a position-based robust visual servoing method which is developed for operation of a human-like robot with two arms. The proposed visual servoing method utilizes SIFT algorithm for object detection and CAMSHIFT algorithm for object tracking. While the conventional CAMSHIFT has been used mainly for object tracking in a 2D image plane, we extend its usage for object tracking in 3D space, by combining the results of CAMSHIFT for two image plane of a stereo camera. This approach shows a robust and dependable result. Once the robot's task is defined based on the extracted 3D information, the robot is commanded to carry out the task. We conduct several position-based visual servoing tasks and compare performances under different conditions. The results show that the proposed visual tracking algorithm is simple but very effective for position-based visual servoing.