Advanced Robotics

Jiang, Xin; Konno, Atsushi; Uchiyama, Masaru

doi: 10.1163/016918610X487072pmid: N/A

This paper discusses a vision-based approach to implement task-level control in flexible-link manipulators. The proposed approach emphasizes the advantage of using vision in the control of flexible manipulators. It is pointed out that taking advantage of the inherent robustness, implementation of an image-based visual servo can be regarded as a synthetic solution to precise task-level control of flexible manipulators. This approach is implemented in a three-dimensional flexible-link manipulator. The implementation makes good use of filters in decoupling task-level control and vibration suppression control. Moreover, we point out that although the robustness of the approach can help to overcome the difficulty in control resulting from the complex measurement of the link's elastic deformation, it lacks in capability of tip trajectory specification. This problem is analyzed in this research and it leads to the proposal for the integration of the image interpolation technique. This technique makes the proposed approach adequate for tasks involved with complex tip trajectories. For flexible-link manipulators, the proposed approach with the remedy is the first vision-based synthetic solution that attempts to make a flexible manipulator usable for a practical task.

Morales, Yoichi; Tsubouchi, Takashi; Yuta, Shinichi

doi: 10.1163/016918610X487081pmid: N/A

This paper presents an approach for vehicle three-dimensional (3-D) localization in outdoor woodland environments where a previously available two-dimensional road centerline map is used in combination with a loosely coupled multi-sensor system to estimate the vehicle position in mountainous forested paths. The localization system is composed of a wheel encoder, an inertial measurement unit, a DGPS, a laser sensor and a barometer. An extended Kalman filter is used for sensor data fusion and pose estimation. When available, DGPS is used for 3-D dead reckoning accumulated error correction. During DGPS blackouts, the laser sensor is used for road extraction and measurement of the displacement of the vehicle to the road centerline, then the position is corrected towards the map. Moreover, the barometer that measures the height difference towards a reference is used to correct the estimated height in absence of DGPS 3-D data. The estimated height is added to the available road map to obtain a 3-D road centerline map that includes the road width measured with the laser sensor. Experimental results in large-scale real mountainous woodland environments show the robustness and simplicity of the proposed approach for vehicle localization and 3-D map extension.

Mombaur, Katja; Laumond, Jean-Paul; Yoshida, Eiichi

doi: 10.1163/016918610X487090pmid: N/A

In this paper we explore the underlying principles of natural locomotion path generation of human beings. The knowledge of these principles is useful to implement biologically inspired path planning algorithms on a humanoid robot. By 'locomotion path' we denote the motion of the robot as a whole in the plane. The key to our approach is to formulate the path planning problem as an optimal control problem. We propose a single dynamic model valid for all situations, which includes both non-holonomic and holonomic modes of locomotion, as well as an appropriately designed unified objective function. The choice between holonomic and non-holonomic behavior is not accomplished by a switching model, but it appears in a smooth way, along with the optimal path, as a result of the optimization by efficient numerical techniques. The proposed model and objective function are successfully tested in six different locomotion scenarios. The resulting paths are implemented on the HRP-2 robot in the simulation environment OpenHRP as well as in the experiment on the real robot.

Wang, Zhongli; Liu, Yunhui

doi: 10.1163/016918610X487108pmid: N/A

In this paper, the stabilization control problem of a lake surface cleaning robot (LSCR) that is driven by a driving and steering mechanism is addressed. Since the LSCR has more degrees of freedom than the number of control inputs, its motion is subject to non-holonomic constraints. Generally, this kind of system cannot be asymptotically stabilized using a time-invariant smooth feedback controller in the Cartesian coordinates. A novel controller using the vector backstepping technique for controlling the position and orientation of the LSCR is presented. We first represent the pose of the LSCR by a polar coordinate system centered at the desired pose and transform the dynamics equation of the LSCR from the Cartesian coordinates to the polar coordinates. Then a feedback control law is derived to yield global asymptotic convergence of the position and orientation of the system to the desired values using the vectorial backstepping design scheme. We prove the asymptotic stability of the system under the control of the proposed method using the Lyapunov theory. Simulations have been carried out to demonstrate the performance of the proposed controller.

Wang, Shigang; Yang, Enhui; Wang, Xinhong; Deng, Qi; Liang, Qinghua; Mo, Jinqiu

doi: 10.1163/016918610X487117pmid: N/A

Based on investigating existing on-line detection methods for energized ceramic post insulators, this paper proposes a new live-line work robot involving ultrasonic detection for flaws in porcelain post insulators at 220-kV high-voltage (HV) substations. Owing to the HV, strong electromagnetic field and space conditions, the robot would be a special one. Thus, on the basis of studying correlative technologies — mechanism design, visual alignment and location, HV insulation, electromagnetic compatibility, automatic control, and wireless communication — each part of the robot system is designed and analyzed. The experiment and trial operation results show that the designed robot can work normally in 220-kV substations, and cracks in porcelain post insulators can be detected effectively, safely and conveniently by the robot.

Kwak, Nosan; Yokoi, Kazuhito; Lee, Beom-Hee

doi: 10.1163/016918610X487126pmid: N/A

In order to solve the simultaneous localization and mapping (SLAM) problem of mobile robots, the Rao–Blackwellized particle filter (RBPF) has been intensively employed. However, it suffers from particle depletion problem, i.e., the number of distinct particles becomes smaller during the SLAM process. As a result, the particles optimistically estimate the SLAM posterior, meaning that particles tend to underestimate their own uncertainty and the filter quickly becomes inconsistent. The main reason of loss of particle diversity is the resampling process of RBPF-SLAM. Standard resampling algorithms for RBPF-SLAM cannot preserve particle diversity due to the behavior of their removing and replicating particles. Thus, we propose rank-based resampling (RBR), which assigns selection probabilities to resample particles based on the rankings of particles. In addition, we provide an extensive analysis on the performance of RBR, including scheduling of resampling. Through the simulation results, we show that the estimation capability of RBPF-SLAM by RBR outperforms that by standard resampling algorithms. More importantly, RBR preserves particle diversity much longer, so it can prevent a certain particle from dominating the particle set and reduce the estimation errors. In addition, through consistency tests, it is shown that RBPF-SLAM by the standard resampling algorithms is optimistically inconsistent, but RBPF-SLAM by RBR is so pessimistically inconsistent that it gives a chance to reduce the estimation errors.

Karimi, Mahmood; Moosavian, S. Ali A.

doi: 10.1163/016918610X487135pmid: N/A

Underactuated manipulators consist of active and passive joints, and developing a control technique that can manage such systems is an attractive, challenging problem. Most works in this area present model-based control laws that require a full dynamics model, and are consequently affected from uncertainties and time delays due to massive computations. Non-model-based control approaches provide an efficient alternative for practical implementation. The Modified Transpose Jacobian (MTJ) algorithm is one of these controllers that has been recently proposed for fully actuated manipulators with a square matrix Jacobian. Based on an approximated feedback linearization approach, the MTJ does not need a priori knowledge of the plant dynamics. In this paper, this scheme is extended to the complicated control problem of underactuated robots in Cartesian space. To this end, the notion of the Transpose Effective Jacobian (TEJ) is presented and so the proposed algorithm is called the Modified TEJ (MTEJ) algorithm. The MTEJ control law employs stored data of the control command in the previous time step, as a learning tool to yield an improved performance. Therefore, the proposed law needs just to a portion of mass matrix that corresponds to passive joint(s), and it is much less affected by inaccuracies in system properties. The gains of the proposed MTEJ can be selected more systematically and do not need to be large; hence, the noise rejection characteristics of the algorithm are improved. Also, no need for the pseudo-inversion of the Jacobian matrix in the proposed controller makes further convenience in the underactuated cases. In addition, the relationship between kinematic and dynamic manipulability measures is discussed for underactuated manipulators. Obtained results show its superior performance even compared to that of the model-based algorithms that need full dynamics models, while the proposed MTEJ requires much lower computation effort.