This paper presents a novel force-cooperative guidance controller design for a walking assistive robot such that it can guide an elderly or handicapped person in an indoor environment. The guidance system has been implemented on a walking helper robot (Walbot) to allow the robot to incorporate passive behaviors. A handrail was provided for Walbot to facilitate passive walking assistance using an omni-directional mobile platform. A laser scanner is used for environment detection and obstacle avoidance. A mass/damper model regulates robot velocity with respect to applied external force. In this paper, we propose a method to fuse output from the compliant motion controller and the autonomous navigation controller in order to give the robotic walker a safe and passive walking guidance. Force-cooperative guidance is achieved by giving proper output-fusing weights to each controller such that the walking help robot can follow the motion intent of the user while avoiding obstacles appearing in the environment.
In this paper, we propose a CAD-based 6-DOF pose estimation design for random bin-picking of multiple different objects using a Kinect RGB-D sensor. 3D CAD models of objects are constructed via a virtual camera, which generates a point cloud database for object recognition and pose estimation. A voxel grid filter is suggested to reduce the number of 3D point cloud of objects for reducing computing time of pose estimation. A voting-scheme method was adopted for the 6-DOF pose estimation a swell as object recognition of different type objects in the bin. Furthermore, an outlier filter is designed to filter out bad matching poses and occluded ones, so that the robot arm always picks up the upper object in the bin to increase pick up success rate. A series of experiments on a Kuka 6-axis robot revels that the proposed system works satisfactorily to pick up all random objects in the bin. The average recognition rate of three different type objects is 93.9% and the pickup success rate is 89.7%.
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