waashk/dblp huggingface dataset:
inverse dynamics of the 3-prr planar parallel robot. recursive modelling for the kinematics and dynamics of the known 3-prr planar parallel robot is established in this paper. three identical planar legs connecting to the moving platform are located in a vertical plane. knowing the motion of the platform, we develop first the inverse kinematics and determine the positions, velocities and accelerations of the robot. further, the principle of virtual work is used in the inverse dynamics problem. several matrix equations offer iterative expressions and graphs for the power requirement comparison of each of three actuators in two different actuation schemes: prismatic actuators and revolute actuators. for the same evolution of the moving platform in the vertical plane, the power distribution upon the three actuators depends on the actuating configuration, but the total power absorbed by the set of three actuators is the same, at any instant, for both driving systems. the study of the dynamics of the parallel mechanisms is done mainly to solve successfully the control of the motion of such robotic systems.
a local approach for bayesian fusion: mathematical analysis and agent based conception. an agent based architecture that is modelled on a successfully operating process of the real world-criminal investigation-circumvents high computational costs caused by bayesian fusion by realising a distributed local bayesian fusion approach. the idea underlying local bayesian fusion approaches is to perform bayesian fusion at least not in detail on the whole space that is spanned by the properties-of-interest. local bayesian fusion is mainly based on coarsening and restriction techniques. here, we focus on coarsening. we give an overview over the agent based conception and translate the proposed ideas in a formal mathematical framework.
analysis of skill acquisition process: a case study of arm reaching task. analysis of continuous process of motor learning gives a lot of useful knowledge for the recovery of human motion activities, and functional adaptability in new environment. this paper proposes a valuation index for degree of proficiency, and shows results of motor skill analysis for several arm reaching tasks. the motor skills were evaluated by using the reproducibility of muscle activation patterns, which were represented by using the variance value of the electromyographic (emg) signal patterns, and the motion accuracy. we confirm that the reproducibility is high when the motion accuracy is high, and the various skill acquisition processes exist due to individual difference. we conclude that, the reproducibility is one of the important indices for evaluating the degree of proficiency.
mutual adaptation among man and machine by using f-mri analysis. a prosthetic device for disabled people requires new and reliable robotics technology. this paper describes the interesting reaction of our brain to an adaptable prosthetic system. the adaptable prosthetic system is composed of an emg signal controlled robot hand with an emg pattern recognition learning function for transradial (below elbow) prostheses. the mutual adaptation between the system and the human body is analyzed using functional magnetic resonance imaging (f-mri) in order to clarify the plasticity of the motor and sensory cortex area according to the changes in the prosthetic system. the developed prosthetic hand has 13 dof: three motors on the thumb, two motors for each finger, and two motors for the wrist. the tactile feedback is applied by using surface electrical stimulus. the f-mri data shows the process of replacement from a phantom limb image to the prosthetic hand image.
hrp-2w: a humanoid platform for research on support behavior in daily life environments. we introduce a concept of a real-world-oriented humanoid robot that can support humans' activities in daily life. in such environments, robots have to watch humans, understand their behavior, and support their daily life tasks. in particular, these robots must be capable of such real-world behavior as handling tableware and delivering daily commodities by hand. we developed a humanoid robot, hrp-2w, which has an upper body of hrp-2 [k. kaneko, f. kanehiro, s. kajita, h. hirukawa, t. kawasaki, m. hirata, k. akachi, t. isozumi, humanoid robot hrp-2, in: proceedings of the 2004 ieee international conference on robotics & automation, 2004, pp. 1083-1090] and a wheel module instead of legs, as a research platform to fulfill this aim. we also developed basic software configuration in order to integrate our platform with other research groups. through experiments, we demonstrated the feasibility of the humanoid robot platform and the potential of the software architecture.
incremental reconstruction of generalized voronoi diagrams on grids. we present an incremental algorithm for constructing and reconstructing generalized voronoi diagrams (gvds) on grids. our algorithm, dynamic brushfire, uses techniques from the path planning community to efficiently update gvds when the underlying environment changes or when new information concerning the environment is received. dynamic brushfire is an order of magnitude more efficient than current approaches. in this paper we present the algorithm, compare it to current approaches on several experimental domains involving both simulated and real data, and demonstrate its usefulness for multirobot path planning.
optic flow-based vision system for autonomous 3d localization and control of small aerial vehicles. the problem considered in this paper involves the design of a vision-based autopilot for small and micro unmanned aerial vehicles (uavs). the proposed autopilot is based on an optic flow-based vision system for autonomous localization and scene mapping, and a nonlinear control system for flight control and guidance. this paper focusses on the development of a real-time 3d vision algorithm for estimating optic flow, aircraft self-motion and depth map, using a low-resolution onboard camera and a low-cost inertial measurement unit (imu). our implementation is based on 3 nested kalman filters (3nkf) and results in an efficient and robust estimation process. the vision and control algorithms have been implemented on a quadrotor uav, and demonstrated in real-time flight tests. experimental results show that the proposed vision-based autopilot enabled a small rotorcraft to achieve fully-autonomous flight using information extracted from optic flow.
policy gradient learning for a humanoid soccer robot. in humanoid robotic soccer, many factors, both at low-level (e.g., vision and motion control) and at high-level (e.g., behaviors and game strategies), determine the quality of the robot performance. in particular, the speed of individual robots, the precision of the trajectory, and the stability of the walking gaits, have a high impact on the success of a team. consequently, humanoid soccer robots require fine tuning, especially for the basic behaviors. in recent years, machine learning techniques have been used to find optimal parameter sets for various humanoid robot behaviors. however, a drawback of learning techniques is time consumption: a practical learning method for robotic applications must be effective with a small amount of data. in this article, we compare two learning methods for humanoid walking gaits based on the policy gradient algorithm. we demonstrate that an extension of the classic policy gradient algorithm that takes into account parameter relevance allows for better solutions when only a few experiments are available. the results of our experimental work show the effectiveness of the policy gradient learning method, as well as its higher convergence rate, when the relevance of parameters is taken into account during learning.
cheap joint probabilistic data association filters in an interacting multiple model design. this paper presents an approach to fuse multiple sensors in an interacting multiple model design. visual features like shadow and symmetry, treated as independent stand-alone virtual sensors, are employed for detection and tracking of vehicles for driver assistance tasks. cheap joint probabilistic data association is utilised to account for the large amount of clutter in the measurements provided by these sensors. special attention is devoted to the different noise characteristics of the measurements. the individual sensors are considered in a sequential manner, leading to a versatile fusion architecture that allows easy integration of further sensor modules.
self-modeling in humanoid soccer robots. in this paper we discuss the applicability, potential benefits, open problems and expected contributions that an emerging set of self-modeling techniques might bring on the development of humanoid soccer robots. the idea is that robots might continuously generate, validate and adjust physical models of their sensorimotor interaction with the world. these models are exploited for adapting behavior in simulation, enhancing the learning skills of a robot with the regular transference of controllers developed in simulation to reality. moreover, these simulations can be used to aid the execution of complex sensorimotor tasks, speed up adaptation and enhance task planning. we present experiments on the generation of behaviors for humanoid soccer robots using the back-to-reality algorithm. general motivations are presented, alternative algorithms are discussed and, most importantly, directions of research are proposed.
optimal pitch map generation for scanning pitch design in selective sampling. the reverse engineering process represents one of the best known methodologies for creating three-dimensional (3d) virtual models starting from physical ones. even if in the last few years its usage has significantly increased, the remarkable involvement of the operator has until now represented a significant constraint for its growth. having regard to the fact that this process, and in particular its first step (that is the acquisition phase), strongly depends on the operator's ability and expertise, this paper aims at proposing a strategy for automatically supporting an ''optimal'' acquisition phase. moreover, the acquisition phase represents the only moment in which there is a direct contact between the virtual model and the physical model. for this reason, designing an ''optimal'' acquisition phase will provide as output an efficient set of morphological data, which will turn out to be extremely useful for the following reverse engineering passages (pre-processing, segmentation, fitting, ...). this scenario drives the researcher to use a selective sampling plan, whose grid dimensions are correlated with the complexity of the local surface region analyzed, instead of a constant one. as a consequence, this work proposes a complete operative strategy which, starting from a first raw preliminary acquisition, will provide a new selective sampling plan during the acquisition phase, in order to allow a deeper and more efficient new scansion. the proposed solution does not require the creation of any intermediate model and relies exclusively on the analysis of the metrological performances of the 3d scanner device and of the morphological behaviour of the surface acquired.
differential evolution solution to the slam problem. a new solution to the simultaneous localization and modelling problem is presented in this paper. the algorithm is based on the stochastic search for solutions in the state space to the global localization problem by means of a differential evolution algorithm. this non linear evolutive filter, called evolutive localization filter (elf), searches stochastically along the state space for the best robot pose estimate. the set of pose solutions (the population) focuses on the most likely areas according to the perception and up to date motion information. the population evolves using the log-likelihood of each candidate pose according to the observation and the motion errors derived from the comparison between observed and predicted data obtained from the probabilistic perception and motion model. the proposed slam algorithm operates in two steps: in the first step the elf filter is used at local level to re-localize the robot based on the robot odometry, the laser scan at a given position and a local map where only a low number of the last scans have been integrated. in the second step, the aligned laser measures and the corrected robot poses are used to detect whether the robot is revisiting a previously crossed area (i.e., a cycle in the robot trajectory exists). once a cycle is detected, the evolutive localization filter is used again to estimate the accumulated residual drift in the detected loop and then to re-estimate the robot poses in order to integrate the sensor measures in the global map of the environment. the algorithm has been tested in different environments to demonstrate the effectiveness, robustness and computational efficiency of the proposed approach.
soccer playing humanoid robots: processing architecture, gait generation and vision system. research on humanoid robotics in mechatronics and automation (ma) laboratory, electrical and computer engineering (ece), national university of singapore (nus) was started at the beginning of this decade. various research prototypes for humanoid robots have been designed and are going through evolution over these years. these humanoids have been successfully participating in various robotic soccer competitions. in this paper, three major research and development aspects of the above humanoid research are discussed. the paper focuses on various practical and theoretical considerations involved in processing architecture, gait generation and vision systems.
a survey of robot learning from demonstration. we present a comprehensive survey of robot learning from demonstration (lfd), a technique that develops policies from example state to action mappings. we introduce the lfd design choices in terms of demonstrator, problem space, policy derivation and performance, and contribute the foundations for a structure in which to categorize lfd research. specifically, we analyze and categorize the multiple ways in which examples are gathered, ranging from teleoperation to imitation, as well as the various techniques for policy derivation, including matching functions, dynamics models and plans. to conclude we discuss lfd limitations and related promising areas for future research.
improving grasp quality evaluation. the capability to equilibrate external wrenches is crucial in optimal grasp planning. this paper presents a new method for evaluating this capability when the external wrench is unknown. two criteria are reformulated using the l"2 distance function, and further transformed into two nonlinear optimization problems. the differentiability of the objective functions and choice of initial conditions for global optimization are discussed. keeping all the merits, that the criteria are applicable to grasps of 3-d objects with any contact types, and that the friction cones are not linearized, this work endows them with several new virtues: (a) their formulation and computation are unified for both force-closure and non-force-closure grasps; (b) they are independent of the choice of coordinate frame and unit; (c) the object geometry is taken into account; (d) the computational efficiency is even higher than some methods by linearizing the friction cones.
a mixed analog-digital vision sensor for detecting objects approaching on a collision course. bio-inspired vision system is a particularly good candidate for navigation of mobile robots and vehicles because of its computational advantages, e.g., low power dissipation and compact hardware. previously, we had designed a mixed analog-digital integrated vision system for collision detection inspired by a locust neuronal circuit model. the response of the system was, however, susceptible to the luminance of approaching objects and the vibratory self-motion of a car when it was installed on a miniature mobile car. in the present study, we developed a new collision detection algorithm to overcome these problems based on robust image-motion detection and applied the algorithm to control a miniature mobile car.
feature fusion for basic behavior unit segmentation from video sequences. it has become increasingly popular to study animal behaviors with the assistance of video recordings. an automated video processing and behavior analysis system is desired to replace the traditional manual annotation. we propose a framework for automatic video based behavior analysis systems, which consists of four major modules: behavior modeling, feature extraction from video sequences, basic behavior unit (bbu) discovery and complex behavior recognition. bbu discovery is performed based on features extracted from video sequences, hence the fusion of multiple dimensional features is very important. in this paper, we explore the application of feature fusion techniques to bbu discovery with one and multiple cameras. we applied the vector fusion (sbp) method, a multi-variate vector visualization technique, in fusing the features obtained from a single camera. this technique reduces the multiple dimensional data into two dimensional (sbp) space, and the spatial and temporal analysis in sbp space can help discover the underlying data groups. then we present a simple feature fusion technique for bbu discovery from multiple cameras with the affinity graph method. finally, we present encouraging results on a physical system and a synthetic mouse-in-a-cage scenario from one, two, and three cameras. the feature fusion methods in this paper are simple yet effective.
hardware design and gait generation of humanoid soccer robot stepper-3d. this paper presents the hardware design and gait generation of humanoid soccer robot stepper-3d. virtual slope walking, inspired by passive dynamic walking, is introduced for gait generation. in virtual slope walking, by actively extending the stance leg and shortening the swing leg, the robot walks on level ground as it walks down a virtual slope. in practical, virtual slope walking is generated by connecting three key frames in the sagittal plane with sinusoids. aiming for improving the walking stability, the parallel double crank mechanism are adopted in the leg structure. experimental results show that stepper-3d achieves a fast forward walking speed of 0.5 m/s and accomplishes omnidirectional walking. stepper-3d performed fast and stable walking in the robocup 2008 humanoid competitions.
a bayesian approach to information fusion for evaluating the measurement uncertainty. the bayesian approach to uncertainty evaluation is a classical example of the fusion of information from different sources. basically, it is founded on both the knowledge about the measurement process and the influencing quantities and parameters. the knowledge about the measurement process is primarily represented by the so-called model equation, which forms the basic relationship for the fusion of all involved quantities. the knowledge about the influencing quantities and parameters is expressed by their degree of belief, i.e. appropriate probability density functions that usually are obtained by utilizing the principle of maximum information entropy and the bayes theorem. practically, the bayesian approach to uncertainty evaluation is put into effect by employing numerical integration techniques, preferably monte-carlo methods. compared to the iso-gum procedure, the bayesian approach does not have any restrictions with respect to nonlinearities and calculation of confidence intervals.
cluster tracking under kinematical constraints using random matrices. collectively moving object clusters are of particular interest in certain applications and have to be tracked as separate aggregated entities consisting of an unknown number of individuals. group targets often will not cause as many detections since there are individual targets in the group due to limited sensor resolution capabilities. in this case, tracking and data association under the 'one target, one detection' assumption are no longer applicable. in this paper, ellipsoidal object extensions are modeled by random matrices, which are treated as additional state variables to be estimated. an important aspect of gmti tracking is the incorporation of context information into the bayesian data processing formalism. here we consider kinematical constraints such as road maps and sensor specific characteristics such as doppler blindness.
characterization of zero tracking error references in the kinematic control of wheeled mobile robots. this work establishes the reference signal conditions for zero tracking error when controlling wheeled mobile robots under the kinematic framework, that is, when the low-level dynamics is neglected. the reference characterization is based on the classical decoupled robot control and the inverse kinematics of fixed, centered orientable, castor and swedish wheels. procedures to avoid tracking error when a particular condition is not satisfied are also indicated. simulations are shown to illustrate the reference conditions for each type of mobile robot and their implications. finally, an industrial forklift is considered in a real situation to validate the previous results and to highlight the limits of the kinematic framework assumption.
multisensor based security robot system for intelligent building. intelligent building can provide safety, convenience, efficiency and entertainment for life in the 21st century. the most importance role of the intelligent building is the security system. we develop a multi sensor-based intelligent security robot (isr) that is widely employed in intelligent buildings. the intelligent security robot can detect abnormal and dangerous situations and notify users. the robot has the shape of cylinder and its diameter, height, and weight are 50 cm, 130 cm and 100 kg respectively. the function of the isr contains six parts. there is the software development system; avoiding obstacle and motion planning system, image system, sensor system, remote supervise system and other systems. we develop a multi sensor-based sensor system in the isr. we use multiple multisensor fusion algorithms to get an exact decision in the detection subsystem of the sensor system. there is an adaptive fusion method, a rule based method, and a statistical signal method. we demonstrate the remote supervisory system to control the isr using a direct control mode and a behavior control mode. we think that the man-machine interface in a security robot system must have mobility and convenience. therefore, we use a touch screen to display the system state, and design a general user interface (gui) to service the user and visitors. the user can remotely control the appliance using a cell phone through a gsm modem, too. the appliance module can feedback reaction results to the user through a cell phone. finally, we implement the fire detection system in the intelligent security robot (chung-cheng-i). if a fire occurs, the intelligent security robot can find out the fire source using the fire detection system. in intruder detection, we program the same scenario to detect the intruder using the intelligent security robot. the intelligent security robot transmits the message of the detection result to the user using a gsm modem for a fire event or intruder, and transmits the detection result to a client computer through the internet.