Shouren Huang

Dynamic compensation by fusing a high-speed actuator and high-speed visual feedback with its application to fast peg-and-hole alignment

This paper presents a dynamic compensation concept to grapple with the dynamic defects of a traditional robot arm, especially while performing high-speed endpoint regulations. The proposed high-speed dynamic compensation concept offers a new point of view for cooperating with a traditional manipulator to realize highly dexterous performance of manipulations. The concept is realized through adoption of a high-speed light-weight actuator as well as endpoint closed loop configured high-speed cameras. The dynamic compensation is analyzed experimentally with 1000 Hz visual feedback and a high-speed finger for a robot arm in the case of one degree of freedom. The advantage of the proposed approach is that the modeling for the robot system’s dynamics is not needed, whereas it is necessary and trivial in order to realize high-speed regulations by traditional approaches. Thus, the control issue becomes easier with the proposed approach. As an application for this concept, fast peg-and-hole alignment with large position and attitude uncertainty is studied. The alignment algorithm is based on a visual compliance strategy. Alignment experiments show that with the proposed concept of dynamic compensation as well as visual compliant motion control, robust and fast convergence was realized for most cases. Graphical Abstract

Automatic Navigation for A Mobile Robot with Monocular Vision

Monocular vision based navigation method has the merits of simple computation and cheap hardware and is promising to realize real time navigation. A monocular vision based navigation method for a mobile robot moving in unknown environment is presented in the paper. By a special installation of a monocular camera on the top of a mobile robot, the method can realize the obstacle detection, distance measurement and path planning based on one single image, so as to realize automatic navigation of a mobile robot in unknown environment. Experiments on the method were done in real environment and it shows that a mobile robot can move automatically and safely under the guide of its monocular vision system.

Fast peg-and-hole alignment using visual compliance

This paper presents a visual compliance strategy to deal with the problem of fast peg-and-hole alignment with large position and attitude uncertainty. With the use of visual compliance and adoption of a light-weight 3-DOF active peg, decoupled alignment for position and attitude is realized. The active peg is capable of high-speed motion and with less dynamic defects than a traditional robot arm. Two high-speed cameras, one configured as eye-in-hand and the other as eye-to-hand are adopted to provide with the task-space feedback. Visual constraints for effecting the visual compliant motion are analyzed. Alignment experiments show that peg-and-hole alignment with the proposed approach could be successfully realized with robust convergence, and on average, the alignment could be realized within 0.7 s in our experimental setting.

Realizing peg-and-hole alignment with one eye-in-hand high-speed camera

In order to deal with the problem of fast peg-and-hole alignment with position and attitude uncertainty, this paper presents a visual servoing approach with a single eye-in-hand high-speed camera. The coupling between the position and attitude alignment as well as the dynamics of robot arm exist as challenging issues for the fast convergence of the alignment process. The proposed motion separation strategy innovatively adopts a high-speed 3-DOF active peg to cooperate with the robot arm under high-speed visual feedback. Alignment experiments show that peg-and-hole alignment with the proposed approach could be successfully realized with fast convergence for most cases.

Applying High-Speed Vision Sensing to an Industrial Robot for High-Performance Position Regulation under Uncertainties

It is traditionally difficult to implement fast and accurate position regulation on an industrial robot in the presence of uncertainties. The uncertain factors can be attributed either to the industrial robot itself (e.g., a mismatch of dynamics, mechanical defects such as backlash, etc.) or to the external environment (e.g., calibration errors, misalignment or perturbations of a workpiece, etc.). This paper proposes a systematic approach to implement high-performance position regulation under uncertainties on a general industrial robot (referred to as the main robot) with minimal or no manual teaching. The method is based on a coarse-to-fine strategy that involves configuring an add-on module for the main robot’s end effector. The add-on module consists of a 1000 Hz vision sensor and a high-speed actuator to compensate for accumulated uncertainties. The main robot only focuses on fast and coarse motion, with its trajectories automatically planned by image information from a static low-cost camera. Fast and accurate peg-and-hole alignment in one dimension was implemented as an application scenario by using a commercial parallel-link robot and an add-on compensation module with one degree of freedom (DoF). Experimental results yielded an almost 100% success rate for fast peg-in-hole manipulation (with regulation accuracy at about 0.1 mm) when the workpiece was randomly placed.

A Pre-Compensation Fuzzy Logic Algorithm Designed for the Dynamic Compensation Robotic System

This paper deals with the issue of non-model-based position regulation for the dynamic compensation robotic system (DCRS), which has been proposed for cooperating with the existing main robotic systems, such as the common serial robotic arms, to accomplish high-speed and accurate manipulations. The dynamic compensation concept is realized by fusing a high-speed & light-weight compensation actuator as well as endpoint closed loop (ECL) configured high-speed cameras. Within the context of the DCRS, the coarse motion, which is realized by the main robotic system, usually gives rise to negative dynamic impact on the compensation actuator that is configured to accomplish the fine motion. Through the analysis of a simplified model for the coupled two-plant system, relative velocity information between the two plants is found to play a role in the first order derivative of the displacement error. With the use of the relative position information from high-speed visual feedback, this paper proposes a new pre-compensation fuzzy logic control (PFLC) approach for control of the compensation actuator. The PFLC method is model-independent and is realized with a cascade fuzzy inference structure that conveniently integrates the relative velocity term between the two plants into the error regulation, and therefore realizes the partial counteraction of the disturbance from the main robot easily without knowing the explicit mathematical models of the system. Comparison works between the proposed PFLC and approaches that take no consideration of the relative velocity information, such as proportional-derivative (PD) control and conventional fuzzy logic control, are conducted. Simulations and experiments show the consistent effectiveness of the proposed approach.

High-performance robotic contour tracking based on the dynamic compensation concept

This paper focuses on high-performance robotic contour tracking under the uncertainties that commonly exist in actual robotic applications. These uncertainties can be attributed to the robot itself (such as modeling errors or mechanical defects like backlash) or to environmental issues (such as calibration errors or misalignment of the workpiece). We propose a non-model-based dynamic compensation approach based on the coarse-to-fine philosophy, which enables contour tracking with both high speed and good accuracy. This is achieved by adopting a methodology in which a main robot performs fast but coarse motion, while an add-on module conducts accurate compensation for the overall uncertainties using a high-speed camera and high-speed compensation actuator. An algorithm called pre-compensated proportionalderivative sliding mode control (pre-compensated PD-SMC) is proposed to control the compensation actuator. The effectiveness of the proposed contour tracking approach and control algorithm are experimentally verified using two typical planar-contour shapes: a random smooth-curvature and rectangle.

Towards assistive human-robot micro manipulation

We propose a robotic system for assistive humanrobot micromanipulation. Using high-speed visual feedback operating at 1 kHz, the robot tracks the workpiece held by a human operator and using this information, it aligns the workpiece to the target which is mounted to the robots actuator. The system is able to track and compensate for errors with an accuracy of less than one micrometer. As an example application, we perform experiments on the peg-in-hole task, where the robot continuously aligns a 70 μm hole, attached to the robot, to a 50 μm peg, held by the operator, in order to facilitate insertion. The results show that the proposed system outperforms the operators performing the same task with magnified visual feedback in terms of both completion time and number of successful insertions. In addition, by using the proposed system the test subjects experienced that they were subject to significantly less mental strain compared to using magnified visual feedback.

A direct visual servo scheme based on simplified interaction matrix for high-speed manipulation

This paper presents a visual servoing approach for high-speed manipulation with one eye-in-hand high-speed vision sensor. By exploiting the special features of high-speed visual feedback and motion, a direct visual servoing scheme based on a simplified interaction matrix is proposed. The cameras internal parameters are not calibrated. Simplifying the interaction matrix allows decoupling of motions, which improves global convergence, as shown by simulations. By further simplifying the interaction matrix so as to make it depth-independent, estimation of depth information is not needed, making the approach suitable for high-speed setpoint control. Simulations were performed to compare the proposed approach with the conventional approach. As applications of the proposed approach, high-speed ball tracking and peg-and-hole alignment experiments were conducted. The results show that the simplified approach worked well for these kinds of manipulation. This paper mainly focuses on translational control; robot arm pose control is ignored because the rotation component of the interaction matrix is independent of the depth information.

Development of an assistive system for position control of a human hand with high speed and high accuracy

Human motion is very flexible for performing various tasks but has low speed and low precision; therefore, support and assistance of human motion by robots is desirable in some situations. In this study, in order to achieve such functions, we developed a new portable module for accurately controlling the position of a human hand and constructed a high-speed, high-accuracy positioning control system using image tracking via a high-speed vision system. In order to evaluate its performance, we executed tracing tests of circular or linear trajectories. Finally, we performed the task of catching a falling ball. Although the task was nearly impossible to perform with the human hand alone, the success rate was dramatically improved by using the proposed method.