Intermittent Connectivity for Exploration in Communication-Constrained Multi-Agent Systems

Motivated by exploration of communication-constrained underground environments using robot teams, we study the problem of planning for intermittent connectivity in multi-agent systems. We propose a novel concept of information-consistency to handle situations where the plan is not initially known by all agents, and suggest an integer linear program for synthesizing information-consistent plans that also achieve auxiliary goals. Furthermore, inspired by network flow problems we propose a novel way to pose connectivity constraints that scales much better than previous methods. In the second part of the paper we apply these results in an exploration setting, and propose a clustering method that separates a large exploration problem into smaller problems that can be solved independently. We demonstrate how the resulting exploration algorithm is able to coordinate a team of ten agents to explore a large environment

Intermittent Connectivity for Exploration in Communication-Constrained Multi-Agent Systems

Motivated by exploration of communication-constrained underground environments using robot teams, we study the problem of planning for intermittent connectivity in multi-agent systems. We propose a novel concept of information-consistency to handle situations where the plan is not initially known by all agents, and suggest an integer linear program for synthesizing information-consistent plans that also achieve auxiliary goals. Furthermore, inspired by network flow problems we propose a novel way to pose connectivity constraints that scales much better than previous methods. In the second part of the paper we apply these results in an exploration setting, and propose a clustering method that separates a large exploration problem into smaller problems that can be solved independently. We demonstrate how the resulting exploration algorithm is able to coordinate a team of ten agents to explore a large environment

Distribuerad Bayesisk Optimering i Multi-Agent System

A variety of engineering problems require extremely resource consuming system performance optimization with an inaccessible system model, some examples include tuning the hyper-parameters in a complex machine learning model, simulation-based aerodynamic design and power system optimization. Bayesian optimization is an approach to solve black-box optimization problems when sample efficiency is of high priority. By parallelizing evaluations, the presence of multiple computing agents can be utilized to solve the optimization problem more efficiently. This thesis address the multi-agent black-box evaluation-expensive optimization problem by enabling distributed Bayesian optimization. Parallel methods proposed in previous research are extended to the distributed setting and a novel approach called Diversity Regularization is developed. Furthermore, motivated by applications in robotics systems such as source seeking, the evaluation-transition trade-off is addressed through regularization. Finally, empirical regret analysis to compare the presented methods on benchmark functions is performed.Många ingenjörsproblem kräver extremt resurskrävande optimering av systemprestanda utan tillgång till en model av systemet, till exempel att ställa in hyperparametrarna i en komplex maskininlärningsmodel, simuleringsbaserad aerodynamiskdesign och optimering av elnät. Bayesisk optimering är en metod föroptimering av svartlådsfunktioner när samplingseffektivitet har hög prioritet. Genom att parallellisera funktionsutvärderingar kan närvaron av flera agenter användas för att lösa optimeringsproblemet mer effektivt. Denna avhandling behandlar optimering av resurskrävande svartlådsfunktioner med flera agenter genom att möjliggöra distribuerad Bayesisk optimering. Parallella metoderföreslagna i tidigare forskning omformuleras till den distribuerade problemformuleringen och e n ny metod som kallas Diversity Regularization presenteras. Dessutom, motiverat av tillämpningar i robotiksystem som källsökning, behandlasavvägningen mellan utvärderingskostnaden och förflyttningskostnaden genom regularisering. Slutligen utförs empirisk analys för att jämföra de presenterade metoderna på referensfunktioner.  

Distribuerad Bayesisk Optimering i Multi-Agent System

A variety of engineering problems require extremely resource consuming system performance optimization with an inaccessible system model, some examples include tuning the hyper-parameters in a complex machine learning model, simulation-based aerodynamic design and power system optimization. Bayesian optimization is an approach to solve black-box optimization problems when sample efficiency is of high priority. By parallelizing evaluations, the presence of multiple computing agents can be utilized to solve the optimization problem more efficiently. This thesis address the multi-agent black-box evaluation-expensive optimization problem by enabling distributed Bayesian optimization. Parallel methods proposed in previous research are extended to the distributed setting and a novel approach called Diversity Regularization is developed. Furthermore, motivated by applications in robotics systems such as source seeking, the evaluation-transition trade-off is addressed through regularization. Finally, empirical regret analysis to compare the presented methods on benchmark functions is performed.Många ingenjörsproblem kräver extremt resurskrävande optimering av systemprestanda utan tillgång till en model av systemet, till exempel att ställa in hyperparametrarna i en komplex maskininlärningsmodel, simuleringsbaserad aerodynamiskdesign och optimering av elnät. Bayesisk optimering är en metod föroptimering av svartlådsfunktioner när samplingseffektivitet har hög prioritet. Genom att parallellisera funktionsutvärderingar kan närvaron av flera agenter användas för att lösa optimeringsproblemet mer effektivt. Denna avhandling behandlar optimering av resurskrävande svartlådsfunktioner med flera agenter genom att möjliggöra distribuerad Bayesisk optimering. Parallella metoderföreslagna i tidigare forskning omformuleras till den distribuerade problemformuleringen och e n ny metod som kallas Diversity Regularization presenteras. Dessutom, motiverat av tillämpningar i robotiksystem som källsökning, behandlasavvägningen mellan utvärderingskostnaden och förflyttningskostnaden genom regularisering. Slutligen utförs empirisk analys för att jämföra de presenterade metoderna på referensfunktioner.  

Autonom omkörning med nåbarhetsanalys och MPC

The era of autonomous cars is on the rise. Asdrivers lose control of the steering wheel, it is crucial that thecars themselves can guarantee safety for all traffic participants.This study aims to design a complete control system that cansafely perform an overtaking maneuver. To guarantee safety ofthe maneuver, reachability calculations will be carried out andanalyzed. The overtaking will be planned by using the modelpredictive control, MPC, framework. To complete the controlsystem a modified proportional controller will be designed totrack the planned path. The control system is implemented inMATLAB and the entire overtaking maneuver is simulated. Theresults show that the designed control framework successfullyperforms the overtaking on a straight two-lane highway in asafe manner.Autonoma bilar är på frammarsch. När förare inte längre har kontroll över ratten är det avgörande att bilarna själva kan garantera säkerheten för alla trafikanter. Denna studie syftar till att utforma ett komplett styrsystem som kan utföra en säker omkörning. Omkörningen planeras med hjälp av ramverket för modell-prediktiv reglering. För att garantera säkerhet används nåbarhetsanalys. Slutligen utformas en modifierad proportionell regulator för att följa den planerade omkörningsvägen. Styrsystemet har implementerats i MATLAB och hela omkörningen har simulerats. Resultaten visar att det konstruerade styrsystemet utför omkörningen på en rak motorväg med två filer på ett säkert och framgångsrikt sätt

Autonom omkörning med nåbarhetsanalys och MPC

The era of autonomous cars is on the rise. Asdrivers lose control of the steering wheel, it is crucial that thecars themselves can guarantee safety for all traffic participants.This study aims to design a complete control system that cansafely perform an overtaking maneuver. To guarantee safety ofthe maneuver, reachability calculations will be carried out andanalyzed. The overtaking will be planned by using the modelpredictive control, MPC, framework. To complete the controlsystem a modified proportional controller will be designed totrack the planned path. The control system is implemented inMATLAB and the entire overtaking maneuver is simulated. Theresults show that the designed control framework successfullyperforms the overtaking on a straight two-lane highway in asafe manner.Autonoma bilar är på frammarsch. När förare inte längre har kontroll över ratten är det avgörande att bilarna själva kan garantera säkerheten för alla trafikanter. Denna studie syftar till att utforma ett komplett styrsystem som kan utföra en säker omkörning. Omkörningen planeras med hjälp av ramverket för modell-prediktiv reglering. För att garantera säkerhet används nåbarhetsanalys. Slutligen utformas en modifierad proportionell regulator för att följa den planerade omkörningsvägen. Styrsystemet har implementerats i MATLAB och hela omkörningen har simulerats. Resultaten visar att det konstruerade styrsystemet utför omkörningen på en rak motorväg med två filer på ett säkert och framgångsrikt sätt

Autonom omkörning med nåbarhetsanalys och MPC

The era of autonomous cars is on the rise. Asdrivers lose control of the steering wheel, it is crucial that thecars themselves can guarantee safety for all traffic participants.This study aims to design a complete control system that cansafely perform an overtaking maneuver. To guarantee safety ofthe maneuver, reachability calculations will be carried out andanalyzed. The overtaking will be planned by using the modelpredictive control, MPC, framework. To complete the controlsystem a modified proportional controller will be designed totrack the planned path. The control system is implemented inMATLAB and the entire overtaking maneuver is simulated. Theresults show that the designed control framework successfullyperforms the overtaking on a straight two-lane highway in asafe manner.Autonoma bilar är på frammarsch. När förare inte längre har kontroll över ratten är det avgörande att bilarna själva kan garantera säkerheten för alla trafikanter. Denna studie syftar till att utforma ett komplett styrsystem som kan utföra en säker omkörning. Omkörningen planeras med hjälp av ramverket för modell-prediktiv reglering. För att garantera säkerhet används nåbarhetsanalys. Slutligen utformas en modifierad proportionell regulator för att följa den planerade omkörningsvägen. Styrsystemet har implementerats i MATLAB och hela omkörningen har simulerats. Resultaten visar att det konstruerade styrsystemet utför omkörningen på en rak motorväg med två filer på ett säkert och framgångsrikt sätt

An Extraterritorial FDA: Could the Food and Drug Administration Apply Its Informed Consent Requirement Abroad Consistent with International Law?

This paper addresses the regulatory challenges wrought by the increasing amount of human subject drug testing conducted in developing countries in support of new drug applications to the Food and Drug Administration. Specifically, it examines the difficulty of enforcing the “informed consent” requirement for ethical scientific research performed in foreign territory. In poorer regions, a lack of government oversight, lower regulatory standards, and barriers to communication have too frequently resulted in allegations of human experimentation performed without its participants’ informed consent. In order to solve this problem, some commentators have suggested that the FDA could apply its human subject protections to foreign clinical research, and enforce them through injunctions or criminal prosecutions. However, the international legal limits on states’ prescriptive jurisdiction may prohibit this exercise of extraterritoriality. After analyzing the proposed extraterritorial regulation of foreign drug testing under the traditional bases and limitations of prescriptive jurisdiction, this paper concludes that such regulation would likely violate international law. However, because nonconsensual clinical research has previously been regarded as a crime against humanity, the FDA might be able to bring criminal prosecutions under the principal of “universal jurisdiction” against investigators or sponsors who conducted studies without their subjects’ informed consent. This analysis offers both positive and normative conclusions regarding the international legal system and the human rights regime