A MULTI-CAMERA VIEW DIRECTION PLANNING STRATEGY FOR MOBILE ROBOTS

2008 ◽  
Vol 05 (04) ◽  
pp. 309-320
Author(s):  
TINGTING XU ◽  
KOLJA KÜHNLENZ ◽  
MARTIN BUSS
Keyword(s):  
Mobile Robots ◽  
Humanoid Robot ◽  
Information Gain ◽  
Dynamic Environments ◽  
Planning Strategy ◽  
Camera View ◽  
Concurrent Tasks ◽  
Individual Task ◽  
Planning Strategies ◽  
The Individual

A multi-camera view direction planning strategy for mobile robots is discussed. Two concurrent tasks for efficient and safe locomotion in dynamic environments are considered: self-localization and dynamic object tracking. The approach is to assign different tasks to different cameras, such that for each task an individual optimal view direction is selected based on information gain maximization. Thereby, the individual task performance is improved significantly. The performance of the proposed strategy is evaluated in simulations considering a humanoid robot navigation scenario and compared with two conventional multi-camera view direction planning strategies.

scholarly journals Learning Innovative Routes for Mobile Robots in Dynamic Partially Unknown Environments

10.5772/5787 ◽  
2005 ◽  
Vol 2 (3) ◽  
pp. 21
Author(s):  
Kristo Heero ◽  
Alvo Aabloo ◽  
Maarja Kruusmaa
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Shortest Path ◽  
Dynamic Environments ◽  
Distance Transform ◽  
Test Results ◽  
Approach To Learning ◽  
Planning Strategy ◽  
Unknown Environments ◽  
Planning Strategies

This paper examines path planning strategies in partially unknown dynamic environemnts and introduces an approach to learning innovative routes. The approach is verified against shortest path planning with a distance transform algorithm, local and global replanning and suboptimal route following in unknown, partially unknown, static and dynamic environments. We show that the learned routes are more reliable and when traversed repeatedly the robot's behaviour becomes more predictable. The test results also suggest that the robot's behaviour depends on knowledge about the environemnt but not about the path planning strategy used.

Hierarchical switching in a multi-dimensional task space is not induced by specific task cues

2001 ◽  
Vol 209 (2) ◽  
pp. 105-117 ◽  
Author(s):  
Thomas Kleinsorge ◽  
Herbert Heuer ◽  
Volker Schmidtke
Keyword(s):  
Specific Task ◽  
Task Space ◽  
Basic Pattern ◽  
Task Representation ◽  
Switching Mechanism ◽  
Factorial Combination ◽  
Individual Task ◽  
The Individual ◽  
The Way

Summary. When participants have to shift between four tasks that result from a factorial combination of the task dimensions judgment (numerical vs. spatial) and mapping (compatible vs. incompatible), a characteristic profile of shift costs can be observed that is suggestive of a hierarchical switching mechanism that operates upon a dimensionally ordered task representation, with judgment on the top and the response on the bottom of the task hierarchy ( Kleinsorge & Heuer, 1999 ). This switching mechanism results in unintentional shifts on lower levels of the task hierarchy whenever a shift on a higher level has to be performed, leading to non-shift costs on the lower levels. We investigated whether this profile depends on the way in which the individual task dimensions are cued. When the cues for the task dimensions were exchanged, the basic pattern of shift costs was replicated with only minor modifications. This indicates that the postulated hierarchical switching mechanism operates independently of the specifics of task cueing.

scholarly journals Computer-assisted contralateral side comparison of the ankle joint using flat panel technology

2021 ◽  
Author(s):  
Sarina Thomas ◽  
Lisa Kausch ◽  
Holger Kunze ◽  
Maxim Privalov ◽  
André Klein ◽  
...  
Keyword(s):  
Information Gain ◽  
Contralateral Side ◽  
Computer Assisted ◽  
Ankle Joints ◽  
Additional Radiation ◽  
Median Position ◽  
Operative Evaluation ◽  
Overall Performance ◽  
The Individual ◽  
Segmentation Problem

Abstract Purpose Reduction and osteosynthesis of ankle fractures is a challenging surgical procedure when it comes to the verification of the reduction result. Evaluation is conducted using intra-operative imaging of the injured ankle and depends on the expertise of the surgeon. Studies suggest that intra-individual variance of the ankle bone shape and pose is considerably lower than the inter-individual variance. It stands to reason that the information gain from the healthy contralateral side can help to improve the evaluation. Method In this paper, an assistance system is proposed that provides a side-to-side view of the two ankle joints for visual comparison and instant evaluation using only one 3D C-arm image. Two convolutional neural networks (CNN) are employed to extract the relevant image regions and pose information of each ankle so that they can be aligned with each other. A first U-Net uses a sliding window to predict the location of each ankle. The standard plane estimation is formulated as segmentation problem so that a second U-Net predicts the three viewing planes for alignment. Results Experiments were conducted to assess the accuracy of the individual steps on 218 unilateral ankle datasets as well as the overall performance on 7 bilateral ankle datasets. The experiments on unilateral ankles yield a median position-to-plane error of $$0.73\pm 1.36$$ 0.73 ± 1.36 mm and a median angular error between 2.98$$^\circ $$ ∘ and 3.71$$^\circ $$ ∘ for the plane normals. Conclusion Standard plane estimation via segmentation outperforms direct pose regression. Furthermore, the complete pipeline was evaluated including ankle detection and subsequent plane estimation on bilateral datasets. The proposed pipeline enables a direct contralateral side comparison without additional radiation. This has the potential to ease and improve the intra-operative evaluation for the surgeons in the future and reduce the need for revision surgery.

scholarly journals Determining Shape and Size of Personal Space of a Human when Passed by a Robot

2021 ◽  
Author(s):  
Margot M. E. Neggers ◽  
Raymond H. Cuijpers ◽  
Peter A. M. Ruijten ◽  
Wijnand A. IJsselsteijn
Keyword(s):  
Mobile Robots ◽  
Humanoid Robot ◽  
Personal Space ◽  
Human Robot Interaction ◽  
Autonomous Mobile Robots ◽  
Robot Interaction ◽  
Human Comfort ◽  
Navigation Algorithms ◽  
Insight Into ◽  
Shape And Size

AbstractAutonomous mobile robots that operate in environments with people are expected to be able to deal with human proxemics and social distances. Previous research investigated how robots can approach persons or how to implement human-aware navigation algorithms. However, experimental research on how robots can avoid a person in a comfortable way is largely missing. The aim of the current work is to experimentally determine the shape and size of personal space of a human passed by a robot. In two studies, both a humanoid as well as a non-humanoid robot were used to pass a person at different sides and distances, after which they were asked to rate their perceived comfort. As expected, perceived comfort increases with distance. However, the shape was not circular: passing at the back of a person is more uncomfortable compared to passing at the front, especially in the case of the humanoid robot. These results give us more insight into the shape and size of personal space in human–robot interaction. Furthermore, they can serve as necessary input to human-aware navigation algorithms for autonomous mobile robots in which human comfort is traded off with efficiency goals.

Prepare: P owe r -Awar e A p proximate Re a l-time Task Scheduling for Ene r gy-Adaptiv e QoS Maximization

2021 ◽  
Vol 20 (5s) ◽  
pp. 1-25
Author(s):  
Shounak Chakraborty ◽  
Sangeet Saha ◽  
Magnus Själander ◽  
Klaus Mcdonald-Maier
Keyword(s):  
Real Time ◽  
Task Scheduling ◽  
Processing Speed ◽  
Empirical Evaluation ◽  
Adaptive Mechanism ◽  
Approximate Computing ◽  
Thermal Safety ◽  
Time Task ◽  
Individual Task ◽  
The Individual

Achieving high result-accuracy in approximate computing (AC) based real-time applications without violating power constraints of the underlying hardware is a challenging problem. Execution of such AC real-time tasks can be divided into the execution of the mandatory part to obtain a result of acceptable quality, followed by a partial/complete execution of the optional part to improve accuracy of the initially obtained result within the given time-limit. However, enhancing result-accuracy at the cost of increased execution length might lead to deadline violations with higher energy usage. We propose Prepare , a novel hybrid offline-online approximate real-time task-scheduling approach, that first schedules AC-based tasks and determines operational processing speeds for each individual task constrained by system-wide power limit, deadline, and task-dependency. At runtime, by employing fine-grained DVFS, the energy-adaptive processing speed governing mechanism of Prepare reduces processing speed during each last level cache miss induced stall and scales up the processing speed once the stall finishes to a higher value than the predetermined one. To ensure on-chip thermal safety, this higher processing speed is maintained only for a short time-span after each stall, however, this reduces execution times of the individual task and generates slacks. Prepare exploits the slacks either to enhance result-accuracy of the tasks, or to improve thermal and energy efficiency of the underlying hardware, or both. With a 70 - 80% workload, Prepare offers 75% result-accuracy with its constrained scheduling, which is enhanced by 5.3% for our benchmark based evaluation of the online energy-adaptive mechanism on a 4-core based homogeneous chip multi-processor, while meeting the deadline constraint. Overall, while maintaining runtime thermal safety, Prepare reduces peak temperature by up to 8.6 °C for our baseline system. Our empirical evaluation shows that constrained scheduling of Prepare outperforms a state-of-the-art scheduling policy, whereas our runtime energy-adaptive mechanism surpasses two current DVFS based thermal management techniques.

scholarly journals A computerized training program for teaching people how to plan better

2017 ◽  
Author(s):  
Falk Lieder ◽  
Paul M. Krueger ◽  
Frederick Callaway ◽  
Tom Griffiths
Keyword(s):  
Training Program ◽  
Intelligent Tutoring System ◽  
Process Tracing ◽  
Optimal Planning ◽  
Immediate Feedback ◽  
Planning Strategy ◽  
Computerized Training ◽  
Planning Strategies ◽  
Process Feedback

We present an intelligent tutoring system for teaching people effective planning strategies. Our training program combines a novel process-tracing paradigm that makes people’s latent planning strategies observable with an AI systems that gives people immediate feedback on how close their planning strategy is to optimal planning. Three experiments demonstrate that our method can automatically discover which planning strategies is optimal for a given class of problems and teach it to people. We find that the metacognitive process feedback provided by our method accelerates learning compared to no-feedback and conventional feedback on the quality of the selected actions, and the training effects are retained after a break even when the feedback is removed.

scholarly journals ERIKA – Early Robotics Introduction at Kindergarten Age

2018 ◽  
Author(s):  
Stefan Schiffer ◽  
Alexander Ferrein
Keyword(s):  
Mobile Robots ◽  
School Children ◽  
Speech Synthesis ◽  
Humanoid Robot ◽  
Human Robot Interaction ◽  
Teaching Tool ◽  
Robot Interaction ◽  
Basic Principles ◽  
Game Show ◽  
Early Introduction

In this work we report on our effort to design and implement an early introduction to basic robotics principles for children at kindergarten age.  The humanoid robot Pepper, which is a great platform for human-robot interaction experiments, was presenting the lecture by reading out the contents to the children making use of its speech synthesis capability.  One of the main challenges of this effort was to explain complex robotics contents in a way that pre-school children could follow the basic principles and ideas using examples from their world of experience. A quiz in a Runaround-game-show style after the lecture activated the children to recap the contents  they acquired about how mobile robots work in principle. Besides the thrill being exposed to a mobile robot that would also react to the children, they were very excited and at the same time very concentrated. What sets apart our effort from other work is that part of the lecturing is actually done by a robot itself and that a quiz at the end of the lesson is done using robots as well. To the best of our knowledge this is one of only few attempts to use Pepper not as a tele-teaching tool, but as the teacher itself in order to engage pre-school children with complex robotics contents. We  got very positive feedback from the children as well as from their educators.

Eine bibliometrische Analyse/PPC and machine learning A bibliometric analysis

2020 ◽  
Vol 110 (04) ◽  
pp. 220-225
Author(s):  
Matthias Schmidt ◽  
Janine Tatjana Maier ◽  
Mark Grothkopp
Keyword(s):  
Machine Learning ◽  
State Of The Art ◽  
Dynamic Environment ◽  
Production Planning And Control ◽  
Manufacturing Companies ◽  
Comprehensive Review ◽  
Planning And Control ◽  
Individual Task ◽  
The Individual ◽  
And Control

Produzierende Unternehmen stehen in einem dynamischen Umfeld vor der Herausforderung eine zunehmende Datenmenge effizienter zu verarbeiten. In diesem Zusammenhang werden häufig Ansätze des maschinellen Lernens (ML) diskutiert. Der Beitrag stellt eine umfassende Aufarbeitung des Stands der Forschung bezogen auf den Einsatz von ML-Ansätzen in der Produktionsplanung und -steuerung (PPS) bereit. Daraus lässt sich der Forschungsbedarf in den einzelnen Aufgabengebieten der PPS ableiten.   In a dynamic environment, manufacturing companies face the challenge of processing an increasing amount of data more efficiently. In this context, approaches of machine learning (ML) are often discussed. This paper provides a comprehensive review of the state of the art regarding the use of ML approaches in production planning and control (PPC). Based on this, the need for research in the individual task areas of PPC can be derived.

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