A Survey of Multi-Robot Motion Planning

Multi-robot Motion Planning (MRMP) is an active research field which has gained attention over the years. MRMP has significant roles to improve the efficiency and reliability of multi-robot system in a wide range of applications from delivery robots to collaborative assembly lines. This survey provides an overview of MRMP taxonomy, state-of-the-art algorithms, and approaches which have been developed for multi-robot systems. This study also discusses the strengths and limitations of each algorithm and their applications in various scenarios. Moreover, based on this, we can draw out open problems for future research.Comment: This is my Ph.D. comprehensive exam repor

Multi-Domain Real-Time Planning in Dynamic Environments

This paper presents a real-time planning framework for multicharacter navigation that enables the use of multiple heterogeneous problem domains of differing complexities for navigation in large, complex, dynamic virtual environments. The original navigation problem is decomposed into a set of smaller problems that are distributed across planning tasks working in these different domains. An anytime dynamic planner is used to efficiently compute and repair plans for each of these tasks, while using plans in one domain to focus and accelerate searches in more complex domains. We demonstrate the benefits of our framework by solving many challenging multi-agent scenarios in complex dynamic environments requiring space-time precision and explicit coordination between interacting agents, by accounting for dynamic information at all stages of the decision-making process

Motion planning for geometric models in data visualization

Interaktivní geometrické modely pro simulaci přírodních jevů (LH11006)Pokročilé grafické a počítačové systémy (SGS-2016-013)A finding of path is an important task in many research areas and it is a common problem solved in a wide range of applications. New problems of finding path appear and complex problems persist, such as a real-time plan- ning of paths for huge crowds in dynamic environments, where the properties according to which the cost of a path is evaluated as well as the topology of paths may change. The task of finding a path can be divided into path planning and motion planning, which implicitly respects the collision with surroundings in the environment. Within the first group this thesis focuses on path planning on graphs for crowds. The main idea is to group members of the crowd by their common initial and target positions and then plan the path for one representative member of each group. These representative members can be navigated by classic approaches and the rest of the group will follow them. If the crowd can be divided into a few groups this way, the proposed approach will save a huge amount of computational and memory demands in dynamic environments. In the second area, motion planning, we are dealing with another problem. The task is to navigate the ligand through the protein or into the protein, which turns out to be a challenging problem because it needs to be solved in 3D with the collision detection

2020 NASA Technology Taxonomy

This document is an update (new photos used) of the PDF version of the 2020 NASA Technology Taxonomy that will be available to download on the OCT Public Website. The updated 2020 NASA Technology Taxonomy, or "technology dictionary", uses a technology discipline based approach that realigns like-technologies independent of their application within the NASA mission portfolio. This tool is meant to serve as a common technology discipline-based communication tool across the agency and with its partners in other government agencies, academia, industry, and across the world

Physically-based sampling for motion planning

Motion planning is a fundamental problem with applications in a wide variety of areas including robotics, computer graphics, animation, virtual prototyping, medical simulations, industrial simulations, and trac planning. Despite being an active area of research for nearly four decades, prior motion planning algorithms are unable to provide adequate solutions that satisfy the constraints that arise in these applications. We present a novel approach based on physics-based sampling for motion planning that can compute collision-free paths while also satisfying many physical constraints. Our planning algorithms use constrained simulation to generate samples which are biased in the direction of the nal goal positions of the agent or agents. The underlying simulation core implicitly incorporates kinematics and dynamics of the robot or agent as constraints or as part of the motion model itself. Thus, the resulting motion is smooth and physically-plausible for both single robot and multi-robot planning. We apply our approach to planning of deformable soft-body agents via the use of graphics hardware accelerated interference queries. We highlight the approach with a case study on pre-operative planning for liver chemoembolization. Next, we apply it to the case of highly articulated serial chains. Through dynamic dimensionality reduction and optimized collision response, we can successfully plan the motion of \\snake-like robots in a practical amount of time despite the high number of degrees of freedom in the problem. Finally, we show the use of the approach for a large number of bodies in dynamic environments. By applying our approach to both global and local interactions between agents, we can successfully plan for thousands of simple robots in real-world scenarios. We demonstrate their application to large crowd simulations

Modeling, Evaluation, and Scale on Artificial Pedestrians: A Literature Review

Modeling pedestrian dynamics and their implementation in a computer are challenging and important issues in the knowledge areas of transportation and computer simulation. The aim of this article is to provide a bibliographic outlook so that the reader may have quick access to the most relevant works related to this problem. We have used three main axes to organize the article's contents: pedestrian models, validation techniques, and multiscale approaches. The backbone of this work is the classification of existing pedestrian models; we have organized the works in the literature under five categories, according to the techniques used for implementing the operational level in each pedestrian model. Then the main existing validation methods, oriented to evaluate the behavioral quality of the simulation systems, are reviewed. Furthermore, we review the key issues that arise when facing multiscale pedestrian modeling, where we first focus on the behavioral scale (combinations of micro and macro pedestrian models) and second on the scale size (from individuals to crowds). The article begins by introducing the main characteristics of walking dynamics and its analysis tools and concludes with a discussion about the contributions that different knowledge fields can make in the near future to this exciting area

Roadmap-Based Techniques for Modeling Group Behaviors in Multi-Agent Systems

Simulating large numbers of agents, performing complex behaviors in realistic environments is a difficult problem with applications in robotics, computer graphics and animation. A multi-agent system can be a useful tool for studying a range of situations in simulation in order to plan and train for actual events. Systems supporting such simulations can be used to study and train for emergency or disaster scenarios including search and rescue, civilian crowd control, evacuation of a building, and many other training situations. This work describes our approach to multi-agent systems which integrates a roadmap-based approach with agent-based systems for groups of agents performing a wide range of behaviors. The system that we have developed is highly customizable and allows us to study a variety of behaviors and scenarios. The system is tunable in the kinds of agents that can exist and parameters that describe the agents. The agents can have any number of behaviors which dictate how they react throughout a simulation. Aspects that are unique to our approach to multi-agent group behavior are the environmental encoding that the agents use when navigating and the extensive usage of the roadmap in our behavioral framework. Our roadmap-based approach can be utilized to encode both basic and very complex environments which include multi- level buildings, terrains and stadiums. In this work, we develop techniques to improve the simulation of multi-agent systems. The movement strategies we have developed can be used to validate agent movement in a simulated environment and evaluate building designs by varying portions of the environment to see the effect on pedestrian flow. The strategies we develop for searching and tracking improve the ability of agents within our roadmap-based framework to clear areas and track agents in realistic environments. The application focus of this work is on pursuit-evasion and evacuation planning. In pursuit-evasion, one group of agents, the pursuers, attempts to find and capture another set of agents, the evaders. The evaders have a goal of avoiding the pursuers. In evacuation planning, the evacuating agents attempt to find valid paths through potentially complex environments to a safe goal location determined by their environmental knowledge. Another group of agents, the directors may attempt to guide the evacuating agents. These applications require the behaviors created to be tunable to a range of scenarios so they can reflect real-world reactions by agents. They also potentially require interaction and coordination between agents in order to improve the realism of the scenario being studied. These applications illustrate the scalability of our system in terms of the number of agents that can be supported, the kinds of realistic environments that can be handled, and behaviors that can be simulated

Where the action is: distributed agency between humans, machines, and programs

"In this paper it is argued that the advanced technologies take part in the course and constellation of human action and that they do this with real effects, not only metaphorically. The first part starts with the search for a useful concept of agency that enables the researcher to describe and classify all activities that contribute to the performance of an action. The concept shall include different levels of human agency as well as different levels of technologies in action. The following chapter treats the consequences that these activations of technologies have for the human-technology-relation. If technologies change their role from passive means into agents and mediators, then the narrow concept of instrumental action should be replaced by a broader concept of inter-agency. This part of the paper culminates in the presentation of a gradual model of agency that can be used to describe and discriminate between different levels and grades of action without any regard to the ontological status of the acting unit, may it be human-like or machine-like. In the second part of the paper the question 'What is the adequate unit of action?' is answered. It starts with a thought experiment about the question: Who is really flying the Airbus? We learn from both views, the humanist's and the technologist's one, that what is usually called action, like flying 240 tourists to Tenerife airport, consists of many distributed actions that have to be coordinated by social organization or technical configuration. The concept of distributed agency is spelled out during three steps: It presupposes many loci of agency, not one actor. It declares the hybrid constellations made of the mixed human and material agencies to the adequate research unit, neither the homogeneous social organizations nor the technical configurations. Finally, a third mode of integration called 'framed interactivity' is elaborated that may emerge between the hierarchical mode of master-slave-relation and the open mode of autonomous systems." (excerpt