scholarly journals Intrinsically Distributed Probabilistic Algorithm for Human–Robot Distance Computation in Collision Avoidance Strategies

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 548
Author(s):  
Marcello Chiurazzi ◽  
Alessandro Diodato ◽  
Irene Vetrò ◽  
Joan Ortega Alcaide ◽  
Arianna Menciassi ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Kinematic Chain ◽  
Maximum Error ◽  
Estimation Accuracy ◽  
Computational Time ◽  
New Paradigm ◽  
Probabilistic Algorithm ◽  
Virtual Forces ◽  
Avoidance Strategies ◽  
Application Requirements

Humans and robots are becoming co-workers, both in industrial and medical applications. This new paradigm raises problems related to human safety. To accomplish and solve this issue, many researchers have developed collision avoidance strategies—mainly relying on potential field approaches—in which attractive and repulsive virtual forces are generated between manipulators and objects within a collaborative workspace. The magnitude of such virtual forces strongly depends on the relative distance between the manipulators and the approaching agents, as well on their relative velocity. In this paper, authors developed an intrinsically distributed probabilistic algorithm to compute distances between the manipulator surfaces and humans, allowing tuning the computational time versus estimation accuracy, based on the application requirements. At each iteration, the algorithm computes the human–robot distances, considering all the Cartesian points within a specific geometrical domain, built around humans’ kinematic chain, and selecting a random subset of points outside of it. Experimental validation was performed in a dynamic and unstructured condition to assess the performance of the algorithm, simulating up to six humans into the shared workspace. Tests showed that the algorithm, with the selected hardware, is able to estimate the distance between the human and the manipulator with a RMSE of 5.93 mm (maximum error of 34.86 mm).

scholarly journals A CONCEPTUAL DESIGN FOR RECONFIGURABLE ROBOTS

2011 ◽  
Author(s):  
Farhad Aghili
Keyword(s):  
Conceptual Design ◽  
Mechanical Design ◽  
Twist Angle ◽  
Kinematic Chain ◽  
Control Synthesis ◽  
Kinematics Analysis ◽  
New Paradigm ◽  
Passive Joint ◽  
Reconfigurable Robots

The paper presents a new paradigm and conceptual design for reconfigurable robots. Unlike conventional reconfigurable robots, our design doesn't achieve reconfigurability by utilizing modular joints. But the robot is equipped with passive joints, i.e. joints with no actuator or sensor, which permit changing the Denavit-Hartenberg (DV) parameters such as the arm length, and the twist angle. The passive joints are controllable when the robot forms a closed kinematic chain. Also each passive joint is equipped with a built-in brake mechanism which is normally locked but it can be released whenever changing of the parameters is required. Kinematics analysis of such a robot plus control synthesis and mechanical design of the brake mechanism are described.

scholarly journals Maximum Closeness Centrality k-Clubs: A Study of Dock-Less Bike Sharing

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Ali Rahim Taleqani ◽  
Chrysafis Vogiatzis ◽  
Jill Hough
Keyword(s):  
Computational Complexity ◽  
Large Scale ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Closeness Centrality ◽  
Computational Time ◽  
Greedy Heuristic ◽  
New Paradigm ◽  
Coordination Costs ◽  
Bike Sharing

In this work, we investigate a new paradigm for dock-less bike sharing. Recently, it has become essential to accommodate connected and free-floating bicycles in modern bike-sharing operations. This change comes with an increase in the coordination cost, as bicycles are no longer checked in and out from bike-sharing stations that are fully equipped to handle the volume of requests; instead, bicycles can be checked in and out from virtually anywhere. In this paper, we propose a new framework for combining traditional bike stations with locations that can serve as free-floating bike-sharing stations. The framework we propose here focuses on identifying highly centralized k-clubs (i.e., connected subgraphs of restricted diameter). The restricted diameter reduces coordination costs as dock-less bicycles can only be found in specific locations. In addition, we use closeness centrality as this metric allows for quick access to dock-less bike sharing while, at the same time, optimizing the reach of service to bikers/customers. For the proposed problem, we first derive its computational complexity and show that it is NP-hard (by reduction from the 3-SATISFIABILITY problem), and then provide an integer programming formulation. Due to its computational complexity, the problem cannot be solved exactly in a large-scale setting, as is such of an urban area. Hence, we provide a greedy heuristic approach that is shown to run in reasonable computational time. We also provide the presentation and analysis of a case study in two cities of the state of North Dakota: Casselton and Fargo. Our work concludes with the cost-benefit analysis of both models (docked vs. dockless) to suggest the potential advantages of the proposed model.

scholarly journals Minimum predicted distance: Applying a common metric to collision avoidance strategies between children and adult walkers

2019 ◽  
Vol 72 ◽  
pp. 16-21 ◽  
Author(s):  
Victoria Rapos ◽  
Michael Cinelli ◽  
Natalie Snyder ◽  
Armel Crétual ◽  
Anne-Hélène Olivier
Keyword(s):  
Collision Avoidance ◽  
Avoidance Strategies

Behavioral strategies of automated vehicles in critical right of way situations on intersections

2015 ◽  
Vol 63 (3) ◽  
Author(s):  
Alexander Stoff ◽  
Hermann Winner
Keyword(s):  
Collision Avoidance ◽  
Behavioral Strategies ◽  
Automated Vehicles ◽  
Right Of Way ◽  
Road Users ◽  
Safety Function ◽  
Potential Safety ◽  
Avoidance Strategies ◽  
The Right

AbstractThis paper analyzes and evaluates alternative options for action and earliest possible dates for intervention for an automated safety function to avoid or mitigate collisions in priority situations in which the right of way regulations are violated by the crossing road users. Based on a simulation of the collision avoidance strategies, the potential safety benefits could be predicted.

Collision avoidance strategies between two athlete walkers: understanding impaired avoidance behaviours in athletes with a previous concussion

2021 ◽  
Author(s):  
Natalie Snyder ◽  
Michael Cinelli ◽  
Victoria Rapos ◽  
Armel Crétual ◽  
Anne-Hélène Olivier
Keyword(s):  
Collision Avoidance ◽  
Avoidance Strategies

scholarly journals 2D wavelet transform data compression with error level guarantee for Z-map models

2017 ◽  
Vol 4 (3) ◽  
pp. 238-247
Author(s):  
Nobuyuki Umezu ◽  
Keisuke Yokota ◽  
Masatomo Inui
Keyword(s):  
Wavelet Transform ◽  
Maximum Error ◽  
Haar Wavelet ◽  
Compression Algorithm ◽  
Computational Time ◽  
Error Level ◽  
Haar Wavelet Transform ◽  
Sample Shape ◽  
Nc Milling ◽  
Reversible Method

Abstract Most of workpiece shapes in NC milling simulations are in Z-map representations that require a very large amount of data to precisely hold a high resolution model. An irreversible compression algorithm for Z-map models using a two-dimensional Haar wavelet transform is proposed to resolve this tight memory situation for an ordinary PC. A shape model is first transformed by using Haar wavelet to build a wavelet synopsis tree while the maximum errors caused by virtually truncating high-frequency components are simultaneously calculated. The total amount of the shape data can be reduced by truncating particular sections of the wavelet components that satisfy the error threshold given by the user. Our algorithm guarantees that any error due to its irreversible compression processes is smaller than the specified level measured against the original model. A series of experiments were conducted using an Apple iMac with a 3.2 GHz CPU and 8 GB of memory. The experiments were performed with 16 sample shape models on 512×512 to 8192×8192 grids to evaluate the compression efficiency of the proposed method. Experimental results confirmed that our compression algorithm requires approximately 20–30 ms for 512×512 models and 7 s for 8192×8192 models under a maximum error level of 10× 10−6 m (a typical criteria for NC milling simulations). The compressed binaries outputted by the proposed method are generally 25–35% smaller than the baseline results by gzip, one of common reversible compression libraries, while these two methods require almost the same level of computational costs. Highlights Discarding diagonal components in WT significantly reduces data amount. The proposed method outperforms a reversible method by 25–35% in size reduction. Most of computational time is consumed by the reversible compression step. The proposed method compresses 5122 models in 20 ms, 81922 models in 7 s.

scholarly journals Derivation of Diagonally Implicit Block Backward Differentiation Formulas for Solving Stiff Initial Value Problems

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Iskandar Shah Mohd Zawawi ◽  
Zarina Bibi Ibrahim ◽  
Khairil Iskandar Othman
Keyword(s):  
Initial Value Problems ◽  
Maximum Error ◽  
Computational Time ◽  
Initial Value ◽  
Stiff Initial Value Problems ◽  
Fully Implicit ◽  
Backward Differentiation Formulas ◽  
The Stability ◽  
Order Four ◽  
Differentiation Formulas

The diagonally implicit 2-point block backward differentiation formulas (DI2BBDF) of order two, order three, and order four are derived for solving stiff initial value problems (IVPs). The stability properties of the derived methods are investigated. The implementation of the method using Newton iteration is also discussed. The performance of the proposed methods in terms of maximum error and computational time is compared with the fully implicit block backward differentiation formulas (FIBBDF) and fully implicit block extended backward differentiation formulas (FIBEBDF). The numerical results show that the proposed method outperformed both existing methods.

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