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This paper deals with the visibility properties of monotone paths connecting two points in the presence of polygonal obstacles. We examine the development of efficient algorithms for constructing a monotone watchman path from which any point on the boundary of obstacles is visible from some point along the path. Specifically, we formulate visibility aware monotone watchman path (VAMWM) problem and...
In manufacturing, the increasing involvement of autonomous robots in production processes poses new challenges on the production management. In this paper we report on the usage of Optimization Modulo Theories (OMT) to solve certain multi-robot scheduling problems in this area. Whereas currently existing methods are heuristic, our approach guarantees optimality for the computed solution. We do not...
This paper introduces a new approach to optimal online motion planning for human-robot interaction scenarios. For a safe, comfortable, and efficient interaction between human and robot working in close proximity, robot motion has to be agile and perceived as natural by the human partner. The robot has to be aware of its environment, including human motions, in order to proactively take actions while...
Learning and planning in partially bservable Markov decision processes (POMDPs) is computationally intractable in real-time system. In order to address this problem, this paper proposes a belief policy reuse (BPR) method to avoid repeated computation. Firstly, the policy reuse evaluation mechanism based on belief Kullback¨CLeibler divergence is presented as a similarity metric between beliefs in the...
This paper presents a method of map building and path planning in an unknown environment. The method employs Light Detection And Ranging (LiDAR) to construct the 2D grid map, on which Anytime D* (AD*) and Dynamic Window Approach (DWA) are used for path planning. The global path is generated by AD* algorithm while DWA is responsible for dynamic obstacle avoidance. Simulation and experiments verify...
In 2017, Teledyne Brown Engineering, Inc. (Teledyne) will begin operations of the five (5)+ year Multi-User System for Earth Sensing (MUSES) mission on the International Space Station (ISS). MUSES is a first of its kind commercial space imaging mission that supports up to four (4) in-flight robotically installed sensors. MUSES will support Teledyne-owned, partner-owned, and tenant sensors for both...
Sampling-based approaches constitute the state-of-the-art for robot motion planning. Collision checking and nearest neighbor search are the major performance bottlenecks of these methods. For an environment with fixed number of obstacles, collision checking for a new candidate state is a constant time operation, whereas nearest neighbor search usually degrades during the runtime of the algorithm....
We present a framework from vision based hand movement prediction in a real-world human-robot collaborative scenario for safety guarantee. We first propose a perception submodule that takes in visual data solely and predicts human collaborator's hand movement. Then a robot trajectory adaptive planning submodule is developed that takes the noisy movement prediction signal into consideration for optimization...
This paper describes a system that can find and lift a specific object in a bin containing piled objects. Such a task is ubiquitous in our daily life, for example, in finding a small toy in a toy box or in finding a stationary in a drawer. To efficiently achieve this task, it is necessary to recognize the object placements with consideration of occlusions and to plan a proper hand motions for lifting...
In this paper, we propose a path planning algorithm targeting an environment with complex and arbitrarily-shaped obstacles. To tackle this issue, we propose a method that adaptively divides a free region into smaller regions of various sizes. The proposed method uses recursive tree traversal and k-means clustering to create regions of diverse sizes according to the distance of the obstacle. Divided...
In order to further expand the sustainability of maritime operations the use of autonomous vehicles has been employed at an increasing scale. This natural increase comes not only in the form of the multiplication of the numbers of the same vehicle model, but also in diversifying the vehicle composition setup in order to allow the exploitation of different types of payloads. Moreover, this use of heterogeneous...
This paper presents a solution for global optimized path planning with respect to finding the shortest distance for autonomous robotic system, particularly in two-dimensional space with a set of obstacles. The proposed approach is based on visibility-graph and the literature review of path planning is presented in details to explain why this approach is used. Through pros, cons, and complexity in...
Autonomous navigation in real-world environments is still a challenging task in many respects. One of the key open challenges is fast planning of physically executable complex maneuvers under non-holonomic constraints. In recent years, lattice-based motion planners have been successfully used to generate kinematically and kinodynamically feasible motions for non-holonomic vehicles. However, it is...
In this paper, a fully-autonomous quadrotor aerial robot for solving the different missions proposed in the 2016 International Micro Air Vehicle (IMAV) Indoor Competition is presented. The missions proposed in the IMAV 2016 competition involve the execution of high-level missions such as entering and exiting a building, exploring an unknown indoor environment, recognizing and interacting with objects,...
The development of deliberative capabilities is required to achieve an intelligent fully autonomous behavior of unmanned aerial systems. An important deliberative capability is the generation of collision-free paths in complex environments. This paper presents a robust real-time collision-free path planner used for the horizontal 2D navigation of multirotor aerial robots in dynamic environments. Its...
This paper explores the problem of path planning under uncertainty. Specifically, we consider online receding horizon based planners that need to operate in a latent environment where the latent information can be modelled via Gaussian Processes. Online path planning in latent environments is challenging since the robot needs to explore the environment to get a more accurate model of latent information...
This paper solves the problem of computing the best grasp in a discrete point set based on a popular grasp quality measure, namely the largest origin-centered ball contained in the grasp wrench set. So far, the solution to this problem is very limited. Noticing that the quality measure for a grasp is equal to the minimum value of the support function of its grasp wrench set over all directions and...
Parts assembly, in a broad sense, is to make multiple objects to be in specific relative poses in contact with each other. One of the major reasons that make it difficult is uncertainty. Because parts assembly involves physical contact between objects, it requires higher precision than other manipulation tasks like collision avoidance. The key idea of this paper is to use simulation-aided physical...
This paper reports on an algorithm for planning trajectories that allow a multirotor micro aerial vehicle (MAV) to quickly identify a set of unknown parameters. In many problems like self calibration or model parameter identification some states are only observable under a specific motion. These motions are often hard to find, especially for inexperienced users. Therefore, we consider system model...
A large number of novel path planning methods for a wide range of problems have been described in literature over the past few decades. These algorithms can often be configured using a set of parameters that greatly influence their performance. In a typical use case, these parameters are only very slightly tuned or even left untouched. Systematic approaches to tune parameters of path planning algorithms...
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