Closed-Form Solution to Controller Design for Human-Robot Interaction

2011 ◽  
Vol 133 (2) ◽  
Author(s):  
Bakir Lacevic ◽  
Paolo Rocco
Keyword(s):  
Parameter Space ◽  
Controller Design ◽  
State Of The Art ◽  
Closed Form Solution ◽  
Realistic Model ◽  
Form Solution ◽  
Human Robot Interaction ◽  
Worst Case Analysis ◽  
Robot Interaction ◽  
Worst Case

This paper deals with controller design for gentle physical human-robot interaction. Two objectives are set up. The first is to establish an analytical framework in order to justify the good features of state of the art controller, recently designed by numerical search of parameter space. The second is to investigate the possibilities to improve the performance of such controller. Our method ensures “prescribed” admittance behavior of the robot, similar to natural admittance controller design but with both more realistic model of the robot and more realistic target admittance. Joining natural admittance approach with the concept of complementary stability allows reaping the benefits of both. Limited knowledge about the environment via structured uncertainty allows a very simple worst-case analysis using elementary tools such as Routh–Hurwitz stability criterion. Consequent relation within the parameters determines an allowed region in the parameter space, where the contact stability is guaranteed. Not surprisingly, on one border of this region, the system behaves exactly the same as when the state of the art controller is employed. In addition, unexpected stability regions are discovered, suggesting theoretical performance improvements.

scholarly journals Question-aware memory network for multi-hop question answering in human–robot interaction

2021 ◽  
Author(s):  
Xinmeng Li ◽  
Mamoun Alazab ◽  
Qian Li ◽  
Keping Yu ◽  
Quanjun Yin
Keyword(s):  
Question Answering ◽  
State Of The Art ◽  
Human Robot Interaction ◽  
Knowledge Graph ◽  
Robot Interaction ◽  
Natural Language Question ◽  
Memory Network ◽  
The Given ◽  
Fine Tune ◽  
Language Question

AbstractKnowledge graph question answering is an important technology in intelligent human–robot interaction, which aims at automatically giving answer to human natural language question with the given knowledge graph. For the multi-relation question with higher variety and complexity, the tokens of the question have different priority for the triples selection in the reasoning steps. Most existing models take the question as a whole and ignore the priority information in it. To solve this problem, we propose question-aware memory network for multi-hop question answering, named QA2MN, to update the attention on question timely in the reasoning process. In addition, we incorporate graph context information into knowledge graph embedding model to increase the ability to represent entities and relations. We use it to initialize the QA2MN model and fine-tune it in the training process. We evaluate QA2MN on PathQuestion and WorldCup2014, two representative datasets for complex multi-hop question answering. The result demonstrates that QA2MN achieves state-of-the-art Hits@1 accuracy on the two datasets, which validates the effectiveness of our model.

scholarly journals User-centred design of humanoid robots’ communication

2020 ◽  
Vol 12 (1) ◽  
pp. 58-73
Author(s):  
Sofia Thunberg ◽  
Tom Ziemke
Keyword(s):  
Mental Models ◽  
Participatory Design ◽  
Humanoid Robot ◽  
State Of The Art ◽  
Design Method ◽  
Humanoid Robots ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Design Concepts ◽  
Design Ideas

AbstractInteraction between humans and robots will benefit if people have at least a rough mental model of what a robot knows about the world and what it plans to do. But how do we design human-robot interactions to facilitate this? Previous research has shown that one can change people’s mental models of robots by manipulating the robots’ physical appearance. However, this has mostly not been done in a user-centred way, i.e. without a focus on what users need and want. Starting from theories of how humans form and adapt mental models of others, we investigated how the participatory design method, PICTIVE, can be used to generate design ideas about how a humanoid robot could communicate. Five participants went through three phases based on eight scenarios from the state-of-the-art tasks in the RoboCup@Home social robotics competition. The results indicate that participatory design can be a suitable method to generate design concepts for robots’ communication in human-robot interaction.

scholarly journals A Dynamic Game Approach for Demand-Side Management: Scheduling Energy Storage with Forecasting Errors

2019 ◽  
Vol 10 (4) ◽  
pp. 897-929 ◽  
Author(s):  
Matthias Pilz ◽  
Luluwah Al-Fagih
Keyword(s):  
Energy Storage ◽  
Closed Form Solution ◽  
Dynamic Game ◽  
Demand Side Management ◽  
Form Solution ◽  
Demand Side ◽  
Case Scenario ◽  
Worst Case ◽  
Time Dynamic ◽  
Forecasting Errors

AbstractSmart metering infrastructure allows for two-way communication and power transfer. Based on this promising technology, we propose a demand-side management (DSM) scheme for a residential neighbourhood of prosumers. Its core is a discrete time dynamic game to schedule individually owned home energy storage. The system model includes an advanced battery model, local generation of renewable energy, and forecasting errors for demand and generation. We derive a closed-form solution for the best response problem of a player and construct an iterative algorithm to solve the game. Empirical analysis shows exponential convergence towards the Nash equilibrium. A comparison of a DSM scheme with a static game reveals the advantages of the dynamic game approach. We provide an extensive analysis on the influence of the forecasting error on the outcome of the game. A key result demonstrates that our approach is robust even in the worst-case scenario. This grants considerable gains for the utility company organising the DSM scheme and its participants.

scholarly journals A Closed-Form Solution for Robust Portfolio Selection with Worst-Case CVaR Risk Measure

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Le Tang ◽  
Aifan Ling
Keyword(s):  
Portfolio Selection ◽  
Risk Measure ◽  
Closed Form Solution ◽  
Efficient Frontier ◽  
Form Solution ◽  
Var Model ◽  
Numerical Comparison ◽  
Worst Case ◽  
Robust Portfolio ◽  
Robust Portfolio Selection

With the uncertainty probability distribution, we establish the worst-case CVaR (WCCVaR) risk measure and discuss a robust portfolio selection problem with WCCVaR constraint. The explicit solution, instead of numerical solution, is found and two-fund separation is proved. The comparison of efficient frontier with mean-variance model is discussed and finally we give numerical comparison with VaR model and equally weighted strategy. The numerical findings indicate that the proposed WCCVaR model has relatively smaller risk and greater return and relatively higher accumulative wealth than VaR model and equally weighted strategy.

A Closed-Form Approach for Optimum Tolerance Allocation of Assemblies with General Tolerance-Cost Function

2011 ◽  
Vol 201-203 ◽  
pp. 1272-1278
Author(s):  
Kuo Ming Cheng ◽  
Jhy Cherng Tsai
Keyword(s):  
Closed Form ◽  
Closed Form Solution ◽  
Form Solution ◽  
Equality Constraints ◽  
Allocation Problem ◽  
Tolerance Allocation ◽  
Lambert W Function ◽  
Manufacturing Cost ◽  
Worst Case ◽  
Constrained Minimization Problems

Tolerancing is one of the most crucial foundations for industry development and an index of product quality and cost. As tolerance allocation is based on manufacturing costs, this paper proposes a comprehensive method for optimal tolerance allocation with minimum manufacturing cost subject to constraints on dimensional chains and machining capabilities. The general reciprocal power and exponential cost-tolerance models with equality constraints as well as the worst-case and statistical tolerancings are employed in this method. A closed-form solution for the optimization problem by applying Lagrange multipliers is derived. The optimal tolerance allocation problem for reciprocal exponential cost-tolerance model by introducing Lambert W function is demonstrated. For constrained minimization problems with only equality constraints, the optimum design can be obtained by solving simultaneous equations without differentiating. An example is illustrated to demonstrate this approach. The result also shows that tolerance can be allocated economically and accurately using this method. The contribution of this paper is to solve the optimal tolerancing allocation problem by an efficient and robust method with simultaneous active constraints.

Controller design for human-robot interaction

2007 ◽  
Vol 24 (2) ◽  
pp. 123-134 ◽  
Author(s):  
Eric Meisner ◽  
Volkan Isler ◽  
Jeff Trinkle
Keyword(s):  
Controller Design ◽  
Human Robot Interaction ◽  
Robot Interaction
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