Physics-based Motion Planning with Temporal Logic Specifications

One of the main foci of robotics is nowadays centered in providing a great degree of autonomy to robots. A fundamental step in this direction is to give them the ability to plan in discrete and continuous spaces to find the required motions to complete a complex task. In this line, some recent approaches describe tasks with Linear Temporal Logic (LTL) and reason on discrete actions to guide sampling-based motion planning, with the aim of finding dynamically-feasible motions that satisfy the temporal-logic task specifications. The present paper proposes an LTL planning approach enhanced with the use of ontologies to describe and reason about the task, on the one hand, and that includes physics-based motion planning to allow the purposeful manipulation of objects, on the other hand. The proposal has been implemented and is illustrated with didactic examples with a mobile robot in simple scenarios where some of the goals are occupied with objects that must be removed in order to fulfill the task.Comment: The 20th World Congress of the International Federation of Automatic Control, 9-14 July 201

Manuver Robot Manual Menggunakan PID pada Robot Manual KRAI 2018

Kontes robot ABU Indonesia mengusung tema ABU Robocon 2018 yaitu Bola Berkah. Dalam tema yang diusung, salah satu robot yang digunakan adalah robot manual yang berfungsi mengambil dan memberikan bola berkah kepada robot otomatis. Robot manual mengalami kesulitan dalam bergerak lurus ketika mengambil dan menyerahkan bola kepada robot otomatis. Ketika berada pada posisi pengambilan dan posisi penyerahan bola, robot yang menggunakan roda omniwheel tidak berada pada posisinya karena terdapat kelembaman. Penerapan Pengendali PID (Proporsional-Integral-Derivatif) yang mendapatkan nilai koreksi dari sensor Rotary Encoder merupakan salah satu solusi yang tepat untuk diimplementasikan pada robot manual. Dengan menggunakan Metode trial and error, PID yang dikembangkan dapat membuat pergerakan robot manual menjadi lebih efisien dan lebih mudah saat dikendalikan oleh operator. Robot Manual menggunakan mikrokontroler Arduino-Due. Hasil pengujian penerapan pada sistem menghasilkan akurasi gerak lurus robot sebesar 60 %, ketepatan posisi mencapai 88 % dengan menggunakan 50% kecepatan putar motor dan akurasi ketepatan posisi mencapai 75% dengan menggunakan 100% kecepatan putar motor.The ABU Indonesia robot contest carries the ABU Robocon 2018 theme, Blessing Ball. In the theme, one of the robots used is a manual robot that functions to take and give a blessing ball to the automatic robot. Manual robots have difficulty in moving straight when taking and handing the ball to an automated robot. When in the taking position and the ball handover position, the robot that uses the Omni wheel is not in position because there is inertia. The application of PID (Proportional-Integral-Derivative) controller which gets the correction value from the Rotary Encoder sensor is one of the right solutions to be implemented in manual robots. By using the trial and error method, the developed PID can make manual robot movements more efficient and easier when controlled by the operator. Manual Robot uses an Arduino-Due microcontroller. The results of testing the application of the system produce an accuracy of 60% straight robot motion, position accuracy reaches 88% using 50% motor rotational speed and accuracy of positioning accuracy reaches 75% using 100% motor rotational speed

A tool for knowledge-oriented physics-based motion planning and simulation

The book covers a variety of topics in Information and Communications Technology (ICT) and their impact on innovation and business. The authors discuss various innovations, business and industrial motivations, and impact on humans and the interplay between those factors in terms of finance, demand, and competition. Topics discussed include the convergence of Machine to Machine (M2M), Internet of Things (IoT), Social, and Big Data. They also discuss AI and its integration into technologies from machine learning, predictive analytics, security software, to intelligent agents, and many more. Contributions come from academics and professionals around the world. Covers the most recent practices in ICT related topics pertaining to technological growth, innovation, and business; Presents a survey on the most recent technological areas revolutionizing how humans communicate and interact; Features four sections: IoT, Wireless Ad Hoc & Sensor Networks, Fog Computing, and Big Data Analytics.(Chapter) The recent advancements in robotic systems set new challenges for robotic simulation software, particularly for planning. It requires the realistic behavior of the robots and the objects in the simulation environment by incorporating their dynamics. Furthermore, it requires the capability of reasoning about the action effects. To cope with these challenges, this study proposes an open-source simulation tool for knowledge-oriented physics-based motion planning by extending The Kautham Project, a C++ based open-source simulation tool for motion planning. The proposed simulation tool provides a flexible way to incorporate the physics, knowledge and reasoning in planning process. Moreover, it provides ROS-based interface to handle the manipulation actions (such as push/pull) and an easy way to communicate with the real robotsPeer ReviewedPostprint (author's final draft

Generation of the global workspace roadmap of the 3-RPR using rotary disk search

Path planning for parallel manipulators in the configuration space can be a challenging task due to the existence of multiple direct kinematic solutions. Hence the aim of this paper is to define a generalised hierarchical path planning scheme for trajectory generation between two configurations in the configuration space for manipulators that exhibit more than one solution in their direct kinematics. This process is applied to the 3-RPR mechanism, constrained to a 2-DOF system by setting active joint parameter ρ1 to a constant. The overall reachable workspace is discretised and deconstructed into smaller patches, which are then stitched together creating a global workspace roadmap. Using the roadmap, path feasibility is obtained and local path planning is used to generate a complete trajectory. This method can determine a singularity-free path between any two connectible points in the configuration space, including assembly mode changes. © 2014 Elsevier Ltd

Manipulation Planning Among Movable Obstacles Using Physics-Based Adaptive Motion Primitives

Robot manipulation in cluttered scenes often requires contact-rich interactions with objects. It can be more economical to interact via non-prehensile actions, for example, push through other objects to get to the desired grasp pose, instead of deliberate prehensile rearrangement of the scene. For each object in a scene, depending on its properties, the robot may or may not be allowed to make contact with, tilt, or topple it. To ensure that these constraints are satisfied during non-prehensile interactions, a planner can query a physics-based simulator to evaluate the complex multi-body interactions caused by robot actions. Unfortunately, it is infeasible to query the simulator for thousands of actions that need to be evaluated in a typical planning problem as each simulation is time-consuming. In this work, we show that (i) manipulation tasks (specifically pick-and-place style tasks from a tabletop or a refrigerator) can often be solved by restricting robot-object interactions to adaptive motion primitives in a plan, (ii) these actions can be incorporated as subgoals within a multi-heuristic search framework, and (iii) limiting interactions to these actions can help reduce the time spent querying the simulator during planning by up to 40x in comparison to baseline algorithms. Our algorithm is evaluated in simulation and in the real-world on a PR2 robot using PyBullet as our physics-based simulator. Supplementary video: \url{https://youtu.be/ABQc7JbeJPM}.Comment: Under review for the IEEE Robotics and Automation Letters (RA-L) journal with conference presentation option at the 2021 International Conference on Robotics and Automation (ICRA). This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

RRT*-SMART: a rapid convergence implementation of RRT*

Many sampling based algorithms have been introduced recently. Among them Rapidly Exploring Random Tree (RRT) is one of the quickest and the most efficient obstacle free path finding algorithm. Although it ensures probabilistic completeness, it cannot guarantee finding the most optimal path. Rapidly Exploring Random Tree Star (RRT*), a recently proposed extension of RRT, claims to achieve convergence towards the optimal solution thus ensuring asymptotic optimality along with probabilistic completeness. However, it has been proven to take an infinite time to do so and with a slow convergence rate. In this paper an extension of RRT*, called as RRT*-Smart, has been prposed to overcome the limitaions of RRT*. The goal of the proposecd method is to accelerate the rate of convergence, in order to reach an optimum or near optimum solution at a much faster rate, thus reducing the execution time. The novel approach of the proposed algorithm makes use of two new techniques in RRT*–Path Optimization and Intelligent Sampling. Simulation results presented in various obstacle cluttered environments along with statistical and mathematical analysis confirm the efficiency of the proposed RRT*-Smart algorithm