A guidance-based docking system has been developed to localize short-range motion of the object of interest (Platform/ Manipulator/ End-effector of the Robot/ Autonomous Vehicle) into the required position with high-precision. Based on line-of-sight (LOS) method and the task-space sensor’s feedback, the LOS Task-Space sensing system has provided sufficient and accurate sensory data for the guidance-based motion planning of the Platform’s (object of interest) translation and rotation in multi-dimensional space. Meanwhile, a model-independent method has been proposed to dock the Platform’s (object of interest) with high precision without calibrating the model.

Figure 1. Three LOS-based Localization System Sketch

This project was expanded to use Neural-Network (NN)-based guidance methodology for path-planning to correct short range motion based on the line-of-sight indirect proximity sensory feedback.

In the project, the NN-model was established to generate the corrective motion commands to reduce the systemic motion errors of the vehicle. The errors were accumulated by a long-range of motions in an iterative manner. The

overall vehicle-docking methodology developed provides effective guidance that is independent of the sensing-system’s calibration model (modeless).

Later, Simulations were conducted with the 3-PSDs-based system. A multi-line-of-sight based guidance method for the six degree-of-freedom (DOF) localization of the platform (end-effector) was developed and applied on the meso-milling machine developed by CIMLab to achieve sub-micron (0.1um) motion planning accuracy. Offsets were measured from the intersection of the three lines-of-sight on each position sensitive detector (PSD) mounted on the platform (end-effector). The errors will then generate corrective motions which guide the tool platform to its desired orientation and position.

Figure 2. LOS-based 3PSD sensors Localization System Setup

From Fig 2, three laser-based LOS are used to define the desired pose (i.e., position and orientation) of the tool platform (end-effector). This guidance algorithm is utilized in a closed-loop system to reduce the measured accumulated errors of the platform after a long-range positioning to a minimum. The three PSDs detected the LOS hits as motion feedback and estimate the actual location of the tool platform (end-effector). The pose estimation algorithm is applied to position the platform iteratively to its desired location. The simulation of this system (3-PSDs-based LOS system) had been completed and proven to minimize the measured location errors to the desired tolerances in a minimal number of iterations.

Figure 3. Magnitude of PSD Offsets with Systematic Error and Random Noise
(PSD Offsets require 4 iterations to converge below noise limits)

Currently, CIMLab is working on a single PSD LOS-based model dependent localization system and has achieved the same desired tolerances as the 3-PSDs-based model.