Effects of temperature and mounting configuration on the dynamic parameters identification of industrial robots

Dynamic parameters are crucial for the definition of high-fidelity models of industrial manipulators. However, since they are often partially unknown, a mathematical model able to identify them is discussed and validated with the UR3 and the UR5 collaborative robots from Universal Robots. According to the acquired experimental data, this procedure allows for reducing the error on the estimated joint torques of about 90% with respect to the one obtained using only the information provided by the manufacturer. The present research also highlights how changes in the robot operating conditions affect its dynamic behavior. In particular, the identification process has been applied to a data set obtained commanding the same trajectory multiple times to both robots under rising joints temperatures. Average reductions of the viscous friction coefficients of about 20% and 17% for the UR3 and the UR5 robots, respectively, have been observed. Moreover, it is shown how the manipulator mounting configuration affects the number of the base dynamic parameters necessary to properly estimate the robots’ joints torques. The ability of the proposed model to take into account different mounting configurations is then verified by performing the identification procedure on a data set generated through a digital twin of a UR5 robot mounted on the ceiling

Learning Probabilistic Generative Models For Fast Sampling-Based Planning

Due to their simplicity and efficiency in high dimensional space, sampling-based motion planners have been gaining interest for robotic manipulation in recent years. We present several new learning approaches using probabilistic generative models for fast sampling-based planning. First, we propose fast collision detection in high dimensional configuration spaces based on Gaussian Mixture Models (GMMs) for Rapidly-exploring Random Trees (RRT). In addition, we introduce a new probabilistically safe local steering primitive based on the probabilistic model. Our local steering procedure is based on a new notion of a convex probabilistically safety corridor that is constructed around a configuration using tangent hyperplanes of confidence ellipsoids of GMMs learned from prior collision history. For efficient sampling, we suggest a sampling method with a learned Q-function with linear function approximation based on feature representations such as Radial Basis Functions. This sampling method chooses the optimal node from which to extend the search tree via the softmax function of learned state values. We also discuss a novel constrained sampling-based motion planning method for grasp and transport tasks with redundant robotic manipulators, which allows the best grasp configuration and approach direction to be automatically determined. Since these approaches with the learned probabilistic models require large size data and time for training, it is essential that they are able to be adapted to environmental change in an online manner. The suggested online learning approach with the Dirichlet Process Mixture Model (DPMM) can adapt the complexity to the data and learn new Gaussian clusters with streaming data in newly explored areas without batch learning. We have applied these approaches in a number of robot arm planning scenarios and have shown their utility and effectiveness in simulation and on a physical 7-DoF robot manipulator

Parallel Real Time RRT*: An RRT* Based Path Planning Process

This thesis presents a new parallelized real-time path planning process. This process is an extension of the Real-Time Rapidly Exploring Random Trees* (RT-RRT*) algorithm developed by Naderi et al in 2015 [1]. The RT-RRT* algorithm was demonstrated on a simulated two-dimensional dynamic environment while finding paths to a varying target state. We demonstrate that the original algorithm is incapable of running at a sufficient rate for control of a 7-degree-of-freedom (7-DoF) robotic arm while maintaining a path planning tree in 7 dimensions. This limitation is due to the complexity of maintaining a tree in a high-dimensional space and the network frequency requirements of the control signal for a real robotic system. We develop and implement a parallelized version of RT-RRT*, dubbed Parallel RT-RRT* (PRT-RRT*), that can update motion plans in a dynamic environment while sending control signals at a high frequency. To achieve this, PRT-RRT* establishes a method of efficient communication between separate collision detection, path planning, and control nodes. We show that PRT-RRT* is capable of solving the dynamic path-planning problem on the 7D Franka Emika Panda robotic arm

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

Integrated Task and Motion Planning of Multi-Robot Manipulators in Industrial and Service Automation

Efficient coordination of several robot arms in order to carry out some given independent/cooperative tasks in a common workspace, avoiding collisions, is an appealing research problem that has been studied in different robotic fields, with industrial and service applications. Coordination of several robot arms in a shared environment is challenging because complexity of collision free path planning increases with the number of robots sharing the same workspace. Although research in different aspects of this problem such as task planning, motion planning and robot control has made great progress, the integration of these components is not well studied in the literature. This thesis focuses on integrating task and motion planning multi-robot-arm systems by introducing a practical and optimal interface layer for such systems. For a given set of speci fications and a sequence of tasks for a multi-arm system, the studied system design aims to automatically construct the necessary waypoints, the sequence of arms to be operated, and the algorithms required for the robots to reliably execute manipulation tasks. The contributions of the thesis are three-fold. First, an algorithm is introduced to integrate task and motion planning layers in order to achieve optimal and collision free task execution. Representation via shared space graph (SSG) is introduced to check whether two arms share certain parts of the workspace and to quantify cooperation of such arm pairs, which is essential in selection of arm sequence and scheduling of each arm in the sequence to perform a task or a sub-task. The introduced algorithm allows robots to autonomously reason about a structured environment, performs the sequence planning of robots to operate, and provides robots and objects path for each task to succeed a set of goals. Secondly, an integrated motion and task planning methodology is introduced for systems of multiple mobile and fixed base robot arms performing different tasks simultaneously in a shared workspace. We introduce concept of dynamic shared space graph (D-SSG) to continuously check whether two arms sharing certain parts of the workspace at different time steps and quantify cooperation of such arm pairs, which is essential to the selection of arm sequences and scheduling of each arm in the sequence to perform a task or a sub-task. The introduced algorithm allows robots to autonomously reason about complex human involving environments to plan the high level decisions (sequence planning) of robots to operate and calculates robots and objects path for each task to succeed a set of goals. The third contribution is design of an integration algorithm between low-level motion planning and high-level symbolic task planning layers to produce alternate plans in case of kinematic and geometric changes in the environment to prevent failure in the high-level task plan. In order to verify the methodological contributions of the thesis with a solid implementation basis, some implementations and tests are presented in the open-source robotics planning environments ROS, Moveit and Gazebo. Detailed analysis of these implementations and test results are provided as well

Perception and manipulation for robot-assisted dressing

Assistive robots have the potential to provide tremendous support for disabled and elderly people in their daily dressing activities. This thesis presents a series of perception and manipulation algorithms for robot-assisted dressing, including: garment perception and grasping prior to robot-assisted dressing, real-time user posture tracking during robot-assisted dressing for (simulated) impaired users with limited upper-body movement capability, and finally a pipeline for robot-assisted dressing for (simulated) paralyzed users who have lost the ability to move their limbs. First, the thesis explores learning suitable grasping points on a garment prior to robot-assisted dressing. Robots should be endowed with the ability to autonomously recognize the garment state, grasp and hand the garment to the user and subsequently complete the dressing process. This is addressed by introducing a supervised deep neural network to locate grasping points. To reduce the amount of real data required, which is costly to collect, the power of simulation is leveraged to produce large amounts of labeled data. Unexpected user movements should be taken into account during dressing when planning robot dressing trajectories. Tracking such user movements with vision sensors is challenging due to severe visual occlusions created by the robot and clothes. A probabilistic real-time tracking method is proposed using Bayesian networks in latent spaces, which fuses multi-modal sensor information. The latent spaces are created before dressing by modeling the user movements, taking the user's movement limitations and preferences into account. The tracking method is then combined with hierarchical multi-task control to minimize the force between the user and the robot. The proposed method enables the Baxter robot to provide personalized dressing assistance for users with (simulated) upper-body impairments. Finally, a pipeline for dressing (simulated) paralyzed patients using a mobile dual-armed robot is presented. The robot grasps a hospital gown naturally hung on a rail, and moves around the bed to finish the upper-body dressing of a hospital training manikin. To further improve simulations for garment grasping, this thesis proposes to update more realistic physical properties values for the simulated garment. This is achieved by measuring physical similarity in the latent space using contrastive loss, which maps physically similar examples to nearby points.Open Acces

A COLLISION AVOIDANCE SYSTEM FOR AUTONOMOUS UNDERWATER VEHICLES

The work in this thesis is concerned with the development of a novel and practical collision avoidance system for autonomous underwater vehicles (AUVs). Synergistically, advanced stochastic motion planning methods, dynamics quantisation approaches, multivariable tracking controller designs, sonar data processing and workspace representation, are combined to enhance significantly the survivability of modern AUVs. The recent proliferation of autonomous AUV deployments for various missions such as seafloor surveying, scientific data gathering and mine hunting has demanded a substantial increase in vehicle autonomy. One matching requirement of such missions is to allow all the AUV to navigate safely in a dynamic and unstructured environment. Therefore, it is vital that a robust and effective collision avoidance system should be forthcoming in order to preserve the structural integrity of the vehicle whilst simultaneously increasing its autonomy. This thesis not only provides a holistic framework but also an arsenal of computational techniques in the design of a collision avoidance system for AUVs. The design of an obstacle avoidance system is first addressed. The core paradigm is the application of the Rapidly-exploring Random Tree (RRT) algorithm and the newly developed version for use as a motion planning tool. Later, this technique is merged with the Manoeuvre Automaton (MA) representation to address the inherent disadvantages of the RRT. A novel multi-node version which can also address time varying final state is suggested. Clearly, the reference trajectory generated by the aforementioned embedded planner must be tracked. Hence, the feasibility of employing the linear quadratic regulator (LQG) and the nonlinear kinematic based state-dependent Ricatti equation (SDRE) controller as trajectory trackers are explored. The obstacle detection module, which comprises of sonar processing and workspace representation submodules, is developed and tested on actual sonar data acquired in a sea-trial via a prototype forward looking sonar (AT500). The sonar processing techniques applied are fundamentally derived from the image processing perspective. Likewise, a novel occupancy grid using nonlinear function is proposed for the workspace representation of the AUV. Results are presented that demonstrate the ability of an AUV to navigate a complex environment. To the author's knowledge, it is the first time the above newly developed methodologies have been applied to an A UV collision avoidance system, and, therefore, it is considered that the work constitutes a contribution of knowledge in this area of work.J&S MARINE LT

The Second Conference on Lunar Bases and Space Activities of the 21st Century, volume 1

These papers comprise a peer-review selection of presentations by authors from NASA, LPI industry, and academia at the Second Conference (April 1988) on Lunar Bases and Space Activities of the 21st Century, sponsored by the NASA Office of Exploration and the Lunar Planetary Institute. These papers go into more technical depth than did those published from the first NASA-sponsored symposium on the topic, held in 1984. Session topics covered by this volume include (1) design and operation of transportation systems to, in orbit around, and on the Moon, (2) lunar base site selection, (3) design, architecture, construction, and operation of lunar bases and human habitats, and (4) lunar-based scientific research and experimentation in astronomy, exobiology, and lunar geology

Library websites popularity: does Facebook really matter?

The purpose of this paper is to determine whether the utilization of social media (Facebook) is an important factor in increasing the visibility of the library site usage in Malaysian public universities. Nine top ranked Malaysian public universities involved in this research and number of Facebook followers for each library website is listed. Alexa software was used as the approach to study the issue of visibility. Alexa is able to determine web site usage, by showing the percentage of visitors of library related subdomain(s) as listed in the top subdomains for each University website (domain) over a month. It is found that Universiti Utara Malaysia library website scored the highest percentage of visitors based on the library related subdomain(s) as listed in the top subdomains for the University website in Alexa. To check such irregularities in access, this paper use EvalAccess 2.0 and it is found that Universiti Sains Malaysia’s library website scored higher irregularities. In term of number of Facebook followers, Univesity of Malaya library has the highest score. It is showed that the utilization of social media (Facebook) is not yet an important factor in increasing the visibility of the library websites. However, expectedly, top ranked universities’ library web sites, are more visible and popular. This research is limited to the situation in Malaysia where public universities are more noticeable and seldom face financial constraints rather than private universities. It is highly important for those universities’ library web sites that are not highly visible to initiate the necessary measures in improving the development of their web sites as the usage of the website is an indicator of online quality

Aerospace Medicine and Biology - A cumulative index to a continuing bibliography

Cumulative index for abstracts of NASA documents on aerospace medicine and biolog