26 research outputs found
Incremental motor skill learning and generalization from human dynamic reactions based on dynamic movement primitives and fuzzy logic system
Different from previous work on single skill learning from human demonstrations, an incremental motor skill learning, generalization and control method based on dynamic movement primitives (DMP) and broad learning system (BLS) is proposed for extracting both ordinary skills and instant reactive skills from demonstrations, the latter of which is usually generated to avoid a sudden danger (e.g., touching a hot cup). The method is completed in three steps. First, ordinary skills are basically learned from demonstrations in normal cases by using DMP. Then the incremental learning idea of BLS is combined with DMP to achieve multi-stylistic reactive skill learning such that the forcing function of the ordinary skills will be reasonably extended into multiple stylistic functions by adding enhancement terms and updating weights of the radial basis function (RBF) kernels. Finally, electromyography (EMG) signals are collected from human muscles and processed to achieve stiffness factors. By using fuzzy logic system (FLS), the two kinds of skills learned are integrated and generalized in new cases such that not only start, end and scaling factors but also the environmental conditions, robot reactive strategies and impedance control factors will be generalized to lead to various reactions. To verify the effectiveness of the proposed method, an obstacle avoidance experiment that enables robots to approach destinations flexibly in various situations with barriers will be undertaken
Mobile Robots Navigation
Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described
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
Advances in Robot Navigation
Robot navigation includes different interrelated activities such as perception - obtaining and interpreting sensory information; exploration - the strategy that guides the robot to select the next direction to go; mapping - the construction of a spatial representation by using the sensory information perceived; localization - the strategy to estimate the robot position within the spatial map; path planning - the strategy to find a path towards a goal location being optimal or not; and path execution, where motor actions are determined and adapted to environmental changes. This book integrates results from the research work of authors all over the world, addressing the abovementioned activities and analyzing the critical implications of dealing with dynamic environments. Different solutions providing adaptive navigation are taken from nature inspiration, and diverse applications are described in the context of an important field of study: social robotics
Proceedings of the NASA Conference on Space Telerobotics, volume 1
The theme of the Conference was man-machine collaboration in space. Topics addressed include: redundant manipulators; man-machine systems; telerobot architecture; remote sensing and planning; navigation; neural networks; fundamental AI research; and reasoning under uncertainty
Proceedings of the NASA Conference on Space Telerobotics, volume 4
Papers presented at the NASA Conference on Space Telerobotics are compiled. The theme of the conference was man-machine collaboration in space. The conference provided a forum for researchers and engineers to exchange ideas on the research and development required for the application of telerobotic technology to the space systems planned for the 1990's and beyond. Volume 4 contains papers related to the following subject areas: manipulator control; telemanipulation; flight experiments (systems and simulators); sensor-based planning; robot kinematics, dynamics, and control; robot task planning and assembly; and research activities at the NASA Langley Research Center
Towards a bionic bat: A biomimetic investigation of active sensing, Doppler-shift estimation, and ear morphology design for mobile robots.
Institute of Perception, Action and BehaviourSo-called CF-FM bats are highly mobile creatures who emit long calls in which much of the
energy is concentrated in a single frequency. These bats face sensor interpretation problems
very similar to those of mobile robots provided with ultrasonic sensors, while navigating in
cluttered environments.
This dissertation presents biologically inspired engineering on the use of narrowband Sonar
in mobile robotics. It replicates, using robotics as a modelling medium, how CF-FM bats process
and use the constant frequency part of their emitted call for several tasks, aiming to improve
the design and use of narrowband ultrasonic sensors for mobile robot navigation.
The experimental platform for the work is RoBat, the biomimetic sonarhead designed by
Peremans and Hallam, mounted on a commercial mobile platform as part of the work reported
in this dissertation. System integration, including signal processing capabilities inspired by the
bat’s auditory system and closed loop control of both sonarhead and mobile base movements,
was designed and implemented. The result is a versatile tool for studying the relationship
between environmental features, their acoustic correlates and the cues computable from them,
in the context of both static, and dynamic real-time closed loop, behaviour.
Two models of the signal processing performed by the bat’s cochlea were implemented,
based on sets of bandpass filters followed by full-wave rectification and low-pass filtering.
One filterbank uses Butterworth filters whose centre frequencies vary linearly across the set.
The alternative filterbank uses gammatone filters, with centre frequencies varying non-linearly
across the set. Two methods of estimating Doppler-shift from the return echoes after cochlear
signal processing were implemented. The first was a simple energy-weighted average of filter
centre frequencies. The second was a novel neural network-based technique. Each method
was tested with each of the cochlear models, and evaluated in the context of several dynamic
tasks in which RoBat was moved at different velocities towards stationary echo sources such
as walls and posts. Overall, the performance of the linear filterbank was more consistent than
the gammatone. The same applies to the ANN, with consistently better noise performance than
the weighted average. The effect of multiple reflectors contained in a single echo was also
analysed in terms of error in Doppler-shift estimation assuming a single wider reflector.
Inspired by the Doppler-shift compensation and obstacle avoidance behaviours found in
CF-FM bats, a Doppler-based controller suitable for collision detection and convoy navigation
in robots was devised and implemented in RoBat. The performance of the controller is satisfactory
despite low Doppler-shift resolution caused by lower velocity of the robot when compared
to real bats.
Barshan’s and Kuc’s 2D object localisation method was implemented and adapted to the geometry of RoBat’s sonarhead. Different TOF estimation methods were tested, the parabola
fitting being the most accurate. Arc scanning, the ear movement technique to recover elevation
cues proposed by Walker, and tested in simulation by her, Peremans and Hallam, was
here implemented on RoBat, and integrated with Barshan’s and Kuc’s method in a preliminary
narrowband 3D tracker.
Finally, joint work with Kim, K¨ampchen and Hallam on designing optimal reflector surfaces
inspired by the CF-FM bat’s large pinnae is presented. Genetic algorithms are used for
improving the current echolocating capabilities of the sonarhead for both arc scanning and IID
behaviours. Multiple reflectors around the transducer using a simple ray light-like model of
sound propagation are evolved. Results show phase cancellation problems and the need of a
more complete model of wave propagation. Inspired by a physical model of sound diffraction
and reflections in the human concha a new model is devised and used to evolve pinnae
surfaces made of finite elements. Some interesting paraboloid shapes are obtained, improving
performance significantly with respect to the bare transducer
E-Learning
Technology development, mainly for telecommunications and computer systems, was a key factor for the interactivity and, thus, for the expansion of e-learning. This book is divided into two parts, presenting some proposals to deal with e-learning challenges, opening up a way of learning about and discussing new methodologies to increase the interaction level of classes and implementing technical tools for helping students to make better use of e-learning resources. In the first part, the reader may find chapters mentioning the required infrastructure for e-learning models and processes, organizational practices, suggestions, implementation of methods for assessing results, and case studies focused on pedagogical aspects that can be applied generically in different environments. The second part is related to tools that can be adopted by users such as graphical tools for engineering, mobile phone networks, and techniques to build robots, among others. Moreover, part two includes some chapters dedicated specifically to e-learning areas like engineering and architecture
Bio-inspired robotic control in underactuation: principles for energy efficacy, dynamic compliance interactions and adaptability.
Biological systems achieve energy efficient and adaptive behaviours through extensive autologous and exogenous compliant interactions. Active dynamic compliances are created and enhanced from musculoskeletal system (joint-space) to external environment (task-space) amongst the underactuated motions. Underactuated systems with viscoelastic property are similar to these biological systems, in that their self-organisation and overall tasks must be achieved by coordinating the subsystems and dynamically interacting with the environment. One important question to raise is: How can we design control systems to achieve efficient locomotion, while adapt to dynamic conditions as the living systems do? In this thesis, a trajectory planning algorithm is developed for underactuated microrobotic systems with bio-inspired self-propulsion and viscoelastic property to achieve synchronized motion in an energy efficient, adaptive and analysable manner. The geometry of the state space of the systems is explicitly utilized, such that a synchronization of the generalized coordinates is achieved in terms of geometric relations along the desired motion trajectory. As a result, the internal dynamics complexity is sufficiently reduced, the dynamic couplings are explicitly characterised, and then the underactuated dynamics are projected onto a hyper-manifold. Following such a reduction and characterization, we arrive at mappings of system compliance and integrable second-order dynamics with the passive degrees of freedom. As such, the issue of trajectory planning is converted into convenient nonlinear geometric analysis and optimal trajectory parameterization. Solutions of the reduced dynamics and the geometric relations can be obtained through an optimal motion trajectory generator. Theoretical background of the proposed approach is presented with rigorous analysis and developed in detail for a particular example. Experimental studies are conducted to verify the effectiveness of the proposed method. Towards compliance interactions with the environment, accurate modelling or prediction of nonlinear friction forces is a nontrivial whilst challenging task. Frictional instabilities are typically required to be eliminated or compensated through efficiently designed controllers. In this work, a prediction and analysis framework is designed for the self-propelled vibro-driven system, whose locomotion greatly relies on the dynamic interactions with the nonlinear frictions. This thesis proposes a combined physics-based and analytical-based approach, in a manner that non-reversible characteristic for static friction, presliding as well as pure sliding regimes are revealed, and the frictional limit boundaries are identified. Nonlinear dynamic analysis and simulation results demonstrate good captions of experimentally observed frictional characteristics, quenching of friction-induced vibrations and satisfaction of energy requirements. The thesis also performs elaborative studies on trajectory tracking. Control schemes are designed and extended for a class of underactuated systems with concrete considerations on uncertainties and disturbances. They include a collocated partial feedback control scheme, and an adaptive variable structure control scheme with an elaborately designed auxiliary control variable. Generically, adaptive control schemes using neural networks are designed to ensure trajectory tracking. Theoretical background of these methods is presented with rigorous analysis and developed in detail for particular examples. The schemes promote the utilization of linear filters in the control input to improve the system robustness. Asymptotic stability and convergence of time-varying reference trajectories for the system dynamics are shown by means of Lyapunov synthesis
Technology 2003: The Fourth National Technology Transfer Conference and Exposition, volume 2
Proceedings from symposia of the Technology 2003 Conference and Exposition, Dec. 7-9, 1993, Anaheim, CA, are presented. Volume 2 features papers on artificial intelligence, CAD&E, computer hardware, computer software, information management, photonics, robotics, test and measurement, video and imaging, and virtual reality/simulation