1,205 research outputs found
Performance of modified jatropha oil in combination with hexagonal boron nitride particles as a bio-based lubricant for green machining
This study evaluates the machining performance of newly developed modified jatropha oils (MJO1, MJO3 and MJO5), both with and without hexagonal boron nitride (hBN) particles (ranging between 0.05 and 0.5 wt%) during turning of AISI 1045 using minimum quantity lubrication (MQL). The experimental results indicated that, viscosity improved with the increase in MJOs molar ratio and hBN concentration. Excellent tribological behaviours is found to correlated with a better machining performance were achieved by MJO5a with 0.05 wt%. The MJO5a sample showed the lowest values of cutting force, cutting temperature and surface roughness, with a prolonged tool life and less tool wear, qualifying itself to be a potential alternative to the synthetic ester, with regard to the environmental concern
Autonomous Visual Servo Robotic Capture of Non-cooperative Target
This doctoral research develops and validates experimentally a vision-based control scheme for the autonomous capture of a non-cooperative target by robotic manipulators for active space debris removal and on-orbit servicing. It is focused on the final capture stage by robotic manipulators after the orbital rendezvous and proximity maneuver being completed. Two challenges have been identified and investigated in this stage: the dynamic estimation of the non-cooperative target and the autonomous visual servo robotic control. First, an integrated algorithm of photogrammetry and extended Kalman filter is proposed for the dynamic estimation of the non-cooperative target because it is unknown in advance. To improve the stability and precision of the algorithm, the extended Kalman filter is enhanced by dynamically correcting the distribution of the process noise of the filter. Second, the concept of incremental kinematic control is proposed to avoid the multiple solutions in solving the inverse kinematics of robotic manipulators. The proposed target motion estimation and visual servo control algorithms are validated experimentally by a custom built visual servo manipulator-target system. Electronic hardware for the robotic manipulator and computer software for the visual servo are custom designed and developed. The experimental results demonstrate the effectiveness and advantages of the proposed vision-based robotic control for the autonomous capture of a non-cooperative target. Furthermore, a preliminary study is conducted for future extension of the robotic control with consideration of flexible joints
Aerial Manipulation: A Literature Review
Aerial manipulation aims at combining the versatil- ity and the agility of some aerial platforms with the manipulation capabilities of robotic arms. This letter tries to collect the results reached by the research community so far within the field of aerial manipulation, especially from the technological and control point of view. A brief literature review of general aerial robotics and space manipulation is carried out as well
Robotic Manipulation and Capture in Space: A Survey
Space exploration and exploitation depend on the development of on-orbit robotic capabilities for tasks such as servicing of satellites, removing of orbital debris, or construction and maintenance of orbital assets. Manipulation and capture of objects on-orbit are key enablers for these capabilities. This survey addresses fundamental aspects of manipulation and capture, such as the dynamics of space manipulator systems (SMS), i.e., satellites equipped with manipulators, the contact dynamics between manipulator grippers/payloads and targets, and the methods for identifying
properties of SMSs and their targets. Also, it presents recent work of sensing pose and system states, of motion planning for capturing a target, and of feedback control methods for SMS during motion or interaction tasks. Finally, the paper reviews major ground testing testbeds for capture operations, and several notable missions and technologies developed for capture of targets on-orbit
Disturbance observer-based neural network control of cooperative multiple manipulators with input saturation
In this paper, the complex problems of internal forces and position control are studied simultaneously and a disturbance observer-based radial basis function neural network (RBFNN) control scheme is proposed to: 1) estimate the unknown parameters accurately; 2) approximate the disturbance experienced by the system due to input saturation; and 3) simultaneously improve the robustness of the system. More specifically, the proposed scheme utilizes disturbance observers, neural network (NN) collaborative control with an adaptive law, and full state feedback. Utilizing Lyapunov stability principles, it is shown that semiglobally uniformly bounded stability is guaranteed for all controlled signals of the closed-loop system. The effectiveness of the proposed controller as predicted by the theoretical analysis is verified by comparative experimental studies
Biomimetic Manipulator Control Design for Bimanual Tasks in the Natural Environment
As robots become more prolific in the human environment, it is important that safe operational
procedures are introduced at the same time; typical robot control methods are
often very stiff to maintain good positional tracking, but this makes contact (purposeful
or accidental) with the robot dangerous. In addition, if robots are to work cooperatively
with humans, natural interaction between agents will make tasks easier to perform with
less effort and learning time. Stability of the robot is particularly important in this
situation, especially as outside forces are likely to affect the manipulator when in a close
working environment; for example, a user leaning on the arm, or task-related disturbance
at the end-effector.
Recent research has discovered the mechanisms of how humans adapt the applied force
and impedance during tasks. Studies have been performed to apply this adaptation to
robots, with promising results showing an improvement in tracking and effort reduction
over other adaptive methods. The basic algorithm is straightforward to implement,
and allows the robot to be compliant most of the time and only stiff when required by
the task. This allows the robot to work in an environment close to humans, but also
suggests that it could create a natural work interaction with a human. In addition, no
force sensor is needed, which means the algorithm can be implemented on almost any
robot.
This work develops a stable control method for bimanual robot tasks, which could also
be applied to robot-human interactive tasks. A dynamic model of the Baxter robot is
created and verified, which is then used for controller simulations. The biomimetic control
algorithm forms the basis of the controller, which is developed into a hybrid control
system to improve both task-space and joint-space control when the manipulator is disturbed
in the natural environment. Fuzzy systems are implemented to remove the need
for repetitive and time consuming parameter tuning, and also allows the controller to
actively improve performance during the task. Experimental simulations are performed,
and demonstrate how the hybrid task/joint-space controller performs better than either
of the component parts under the same conditions. The fuzzy tuning method is then applied
to the hybrid controller, which is shown to slightly improve performance as well as
automating the gain tuning process. In summary, a novel biomimetic hybrid controller
is presented, with a fuzzy mechanism to avoid the gain tuning process, finalised with a
demonstration of task-suitability in a bimanual-type situation.EPSR
Contemporary Robotics
This book book is a collection of 18 chapters written by internationally recognized experts and well-known professionals of the field. Chapters contribute to diverse facets of contemporary robotics and autonomous systems. The volume is organized in four thematic parts according to the main subjects, regarding the recent advances in the contemporary robotics. The first thematic topics of the book are devoted to the theoretical issues. This includes development of algorithms for automatic trajectory generation using redudancy resolution scheme, intelligent algorithms for robotic grasping, modelling approach for reactive mode handling of flexible manufacturing and design of an advanced controller for robot manipulators. The second part of the book deals with different aspects of robot calibration and sensing. This includes a geometric and treshold calibration of a multiple robotic line-vision system, robot-based inline 2D/3D quality monitoring using picture-giving and laser triangulation, and a study on prospective polymer composite materials for flexible tactile sensors. The third part addresses issues of mobile robots and multi-agent systems, including SLAM of mobile robots based on fusion of odometry and visual data, configuration of a localization system by a team of mobile robots, development of generic real-time motion controller for differential mobile robots, control of fuel cells of mobile robots, modelling of omni-directional wheeled-based robots, building of hunter- hybrid tracking environment, as well as design of a cooperative control in distributed population-based multi-agent approach. The fourth part presents recent approaches and results in humanoid and bioinspirative robotics. It deals with design of adaptive control of anthropomorphic biped gait, building of dynamic-based simulation for humanoid robot walking, building controller for perceptual motor control dynamics of humans and biomimetic approach to control mechatronic structure using smart materials
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