On modern construction sites, guidance and automation systems are increasingly applied to excavators. Recently, studies have been actively conducted to compare the estimation results of the bucket tip with the motion measurement method of the boom, stick, and bucket and the sensor selection. This study selected the method of measuring the cylinder length of boom, stick, and bucket, and the method of directly measuring the boom, arm, and bucket, which are commonly used in guidance and automation systems. A low-cost sensor that can be attached and detached to the excavator in modular form was selected to apply the above methods to commercial excavator. After the sensor selection, hardware and excavator simulation models for sensor measurements were constructed. Finally, the trajectory of the bucket tip was compared and analyzed through graphs and simulation results when the boom, stick, and bucket were independently rotated one by one, or together. The results gives a guideline on what kinds of sensors would be better in machine guidance or controlling an excavator according to given external environments.

An object can be gripped firmly through power grasping, in which the gripper fingers and palm are wrapped around the object. However, it is difficult to power-grasp an object if it is placed on a support surface and the grasping point is near the support surface. Because there is no gap between the object and the support surface, the gripper fingers and the support surface will collide when the gripper attempts to power-grasp the object. To address this, we propose a pre-grasp manipulation planning method that uses two robot arms, whereby space can be secured for power grasping by rotating the object while being supported against the support surface. The objects considered in this study are appropriately shaped for a power grasp, but power grasping cannot be performed directly because the desired power-grasping location is close to the support surface on which the object is placed. First, to power-grasp the object, candidate rotation axes on the object and in contact with the support surface are derived based on a mesh model of the object. Then, for each such axis, the object pose that allows power grasping is obtained. Finally, according to the obtained object pose, the paths for rotating and power-grasping the object are planned. We evaluate the proposed approach through simulations and experiments using two UR5e robot arms with a 2F-85 gripper.

This study investigated methods for interpreting sheet music data and converting them into control variables for robots to play the piano. Previous research has addressed the timing and duration of key presses but has not clearly defined the initiation of actions from the perspective of the robot. In addition, the relationship between key press speed and velocity values from the musical instrument digital interface has not adequately addressed sound intensity. Therefore, this research proposes a method for converting musical symbols into control variables, defining the timing of each robot action, and linking key press speed to sound intensity for precise volume control. The study details the timing of the movements of the robot’s fingers and arms and adjusts pedaling according to temporal variations in piano performance. The proposed methods was validated through experiments using a cartesian robot with two hands. The experimental results confirm that the method effectively controls timing and volume of the robot’s play. This study analyzes the impact of varying musical symbols on performance through experiments and suggests their applicability to various robotic forms for piano playing.