Lars Karlsson

AAAI Conference 2017 Conference Paper

Configuration Planning with Temporal Constraints

• Uwe Kšckemann
• Lars Karlsson

Configuration planning is a form of task planning that takes into consideration both causal and information dependencies in goal achievement. This type of planning is interesting, for instance, in smart home environments which contain various sensors and robots to provide services to the inhabitants. Requests for information, for instance from an activity recognition system, should cause the smart home to configure itself in such a way that all requested information will be provided when it is needed. This paper addresses temporal configuration planning in which information availability and goals are linked to temporal intervals which are subject to constrains. Our solutions are based on constraint-based planning which uses different types of constraints to model different types of knowledge. We propose and compare two approaches to configuration planning. The first one models information via conditions and effects of planning operators and essentially reduces configuration planning to constraint-based temporal planning. The second approach solves information dependencies separately from task planning and optimizes the cost of reaching individual information goals. We compare these approaches in terms of the time it takes to solve problems and the quality of the solutions they provide.

AIJ Journal 2017 Journal Article

Geometric backtracking for combined task and motion planning in robotic systems

• Julien Bidot
• Lars Karlsson
• Fabien Lagriffoul
• Alessandro Saffiotti

AAAI Conference 2014 Conference Paper

Grandpa Hates Robots – Interaction Constraints for Planning in Inhabited Environments

• Uwe Koeckemann
• Federico Pecora
• Lars Karlsson

IROS Conference 2012 Conference Paper

Constraint propagation on interval bounds for dealing with geometric backtracking

• Fabien Lagriffoul
• Dimitar Dimitrov 0001
• Alessandro Saffiotti
• Lars Karlsson

The combination of task and motion planning presents us with a new problem that we call geometric backtracking. This problem arises from the fact that a single symbolic state or action may be geometrically instantiated in infinitely many ways. When a symbolic action cannot be geometrically validated, we may need to backtrack in the space of geometric configurations, which greatly increases the complexity of the whole planning process. In this paper, we address this problem using intervals to represent geometric configurations, and constraint propagation techniques to shrink these intervals according to the geometric constraints of the problem. After propagation, either (i) the intervals are shrunk, thus reducing the search space in which geometric backtracking may occur, or (ii) the constraints are inconsistent, indicating the non-feasibility of the sequence of actions without further effort. We illustrate our approach on scenarios in which a two-arm robot manipulates a set of objects, and report experiments that show how the search space is reduced.

TIST Journal 2010 Journal Article

Human-aware task planning

• Marcello Cirillo
• Lars Karlsson
• Alessandro Saffiotti

Consider a house cleaning robot planning its activities for the day. Assume that the robot expects the human inhabitant to first dress, then have breakfast, and finally go out. Then, it should plan not to clean the bedroom while the human is dressing, and to clean the kitchen after the human has had breakfast. In general, robots operating in inhabited environments, like households and future factory floors, should plan their behavior taking into account the actions that will be performed by the humans sharing the same environment. This would improve human-robot cohabitation, for example, by avoiding undesired situations for the human. Unfortunately, current task planners only consider the robot's actions and unexpected external events in the planning process, and cannot accommodate expectations about the actions of the humans. In this article, we present a human-aware planner able to address this problem. Our planner supports alternative hypotheses of the human plan, temporal duration for the actions of both the robot and the human, constraints on the interaction between robot and human, partial goal achievement and, most importantly, the possibility to use observations of human actions in the policy generated for the robot. Our planner has been tested both as a stand-alone component and within a full framework for human-robot interaction in a real environment.

ICAPS Conference 2009 Conference Paper

A Human-Aware Robot Task Planner

• Marcello Cirillo
• Lars Karlsson
• Alessandro Saffiotti

The growing presence of household robots in inhabited environments arises the need for new robot task planning techniques. These techniques should take into consideration not only the actions that the robot can perform or unexpected external events, but also the actions performed by a human sharing the same environment, in order to improve the cohabitation of the two agents, e. g. , by avoiding undesired situations for the human. In this paper, we present a human-aware planner able to address this problem. This planner supports alternative hypotheses of the human plan, temporal duration for the actions of both the robot and the human, constraints on the interaction between robot and human, partial goal achievement and, most importantly, the possibility to use observations of human actions in the policy generated for the robot. The planner has been tested as a standalone component and in conjunction with our framework for human-robot interaction in a real environment.

ECAI Conference 2008 Conference Paper

Automatic Configuration of Multi-Robot Systems: Planning for Multiple Steps

• Robert Lundh
• Lars Karlsson
• Alessandro Saffiotti

We consider multi-robot systems where robots need to cooperate tightly by sharing functionalities with each other. There are methods for automatically configuring a multi-robot system for tight cooperation, but they only produce a single configuration. In this paper, we show how methods for automatic configuration can be integrated with methods for task planning in order to produce a complete plan were each step is a configuration. We also consider the issues of monitoring and replanning in this context, and we demonstrate our approach on a real multi-robot system, the PEIS-Ecology.

IROS Conference 2007 Conference Paper

Dynamic self-configuration of an ecology of robots

• Robert Lundh
• Lars Karlsson
• Alessandro Saffiotti

There is a tendency today toward the study of distributed systems consisting of many heterogeneous, networked, cooperating robotic devices. We refer to a system of this type as an ecology of robots. We call functional configuration of this ecology a way to allocate and connect functionalities among its robots. In general, the same ecology can perform different tasks by using different configuration. Moreover, the same task can often be solved using different configurations, and which is the best one depends on the available resources. This potential flexibility of a robot ecology is reduced by the fact that, in most current approaches, configurations are pre-programmed by hand. In this paper, we propose a plan-based approach to automatically generate a preferred configuration of a robot ecology given a task, environment, and set of resources. In contrast to previous approaches, the state of the ecology is automatically acquired at planning time, and it is monitored during execution in order to reconfigure if a functionality fails. We illustrate these ideas on a specific instance of an ecology of robots, called PEIS Ecology. We also show an experiment run on our PEIS Ecology testbed, in which a robot needs to reconfigure when the original configuration fails.

IROS Conference 2007 Conference Paper

Handling uncertainty in semantic-knowledge based execution monitoring

• Abdelbaki Bouguerra
• Lars Karlsson
• Alessandro Saffiotti

Executing plans by mobile robots, in real world environments, faces the challenging issues of uncertainty and environment dynamics. Thus, execution monitoring is needed to verify that plan actions are executed as expected. Semantic domain-knowledge has been proposed as a source of information to derive and monitor implicit expectations of executing actions. For instance, when a robot moves into a room asserted to be an office, it would expect to see a desk and a chair. We propose to extend the semantic knowledge-based execution monitoring to take uncertainty in actions and sensing into account when verifying the expectations derived from semantic knowledge. We consider symbolic probabilistic action models, and show how semantic knowledge is used together with a probabilistic sensing model in the monitoring process of such actions. Our approach is illustrated by showing test scenarios run in an indoor environment using a mobile robot.

ICRA Conference 2007 Conference Paper

Plan-Based Configuration of an Ecology of Robots

• Robert Lundh
• Lars Karlsson
• Alessandro Saffiotti

We consider an ecology of robots in which robots can help each other by offering information-producing functionalities. A functional configuration of this ecology is a way to allocate and connect functionalities among the participating robots. In general, different configurations can be used to solve the same task, depending on the current situation, and some tasks require sequences of different configurations to be solved. In this paper, we propose a plan-based approach to automatically generate a preferred configuration for a given task, environment, and set of resources. We also describe how our configuration planner can be integrated with an action planner to deal with tasks that require sequences of configurations. We illustrate these ideas on a specific instance of an ecology of robots, called a PEIS Ecology. We also show an experiment run on our PEIS Ecology testbed, in which a sequence of configurations for an olfactory task is automatically generated and executed.

ICRA Conference 2007 Conference Paper

Semantic Knowledge-Based Execution Monitoring for Mobile Robots

• Abdelbaki Bouguerra
• Lars Karlsson
• Alessandro Saffiotti

We describe a novel intelligent execution monitoring approach for mobile robots acting in indoor environments such as offices and houses. Traditionally, monitoring execution in mobile robotics amounted to looking for discrepancies between the model-based predicted state of executing an action and the real world state as computed from sensing data. We propose to employ semantic knowledge as a source of information to monitor execution. The key idea is to compute implicit expectations, from semantic domain information, that can be observed at run time by the robot to make sure actions are executed correctly. We present the semantic knowledge representation formalism, and how semantic knowledge is used in monitoring. We also describe experiments run in an indoor environment using a real mobile robot.

ECAI Conference 2006 Conference Paper

Plan-Based Configuration of a Group of Robots

• Robert Lundh
• Lars Karlsson
• Alessandro Saffiotti

We consider groups of autonomous robots in which robots can help each other by offering information-producing functionalities. A functional configuration is a way to allocate and connect functionalities among robots. In general, different configurations can be used to solve the same task, depending on the current situation. In this paper, we define the idea of functional configuration, and we propose a plan-based approach to automatically generate a preferred configuration for a given task, environment, and set of resources. To illustrate these ideas, we show a simple experiment in which two robots mutually help each-other to cross a door.

ECAI Conference 2006 Conference Paper

Situation Assessment for Sensor-Based Recovery Planning

• Abdelbaki Bouguerra
• Lars Karlsson
• Alessandro Saffiotti

We present an approach for recovery from perceptual failures, or more precisely anchoring failures. Anchoring is the problem of connecting symbols representing objects to sensor data corresponding to the same objects. The approach is based on using planning, but our focus is not on the plan generation per se. We focus on the very important aspect of situation assessment and how it is carried out for recovering from anchoring failures. The proposed approach uses background knowledge to create hypotheses about world states and handles uncertainty in terms of probabilistic belief states. This work is relevant both from the perspective of developing the anchoring framework, and as a study in plan-based recovery from epistemic failures in mobile robots. Experiments on a mobile robot are shown to validate the applicability of the proposed approach.

AAAI Conference 2005 Conference Paper

Recovery Planning for Ambiguous Cases in Perceptual Anchoring

• Mathias Broxvall
• Lars Karlsson

An autonomous robot using symbolic reasoning, sensing and acting in a real environment needs the ability to create and maintain the connection between symbols representing objects in the world and the corresponding perceptual representations given by its sensors. This connection has been named perceptual anchoring. In complex environments, anchoring is not always easy to establish: the situation may often be ambiguous as to which percept actually corresponds to a given symbol. In this paper, we extend perceptual anchoring to deal robustly with ambiguous situations by providing general methods for detecting them and recovering from them. We consider different kinds of ambiguous situations and present planning-based methods to recover from them. We illustrate our approach by showing experiments involving a mobile robot equipped with a color camera and an electronic nose.

IROS Conference 2004 Conference Paper

Putting olfaction into action: using an electronic nose on a multi-sensing mobile robot

• Amy Loutfi
• Silvia Coradeschi
• Lars Karlsson
• Mathias Broxvall

Olfaction is a challenging new sensing modality for intelligent systems. With the emergence of electronic noses it is now possible to detect and recognise a range of different odours for a variety of applications. An existing application is to use electronic olfaction on mobile robots for the purpose of odour based navigation. In this work, we introduce a new application where electronic olfaction is used in cooperation with other types of sensors on a mobile robot in order to acquire the odour property of objects. The mobility of the robot facilitates the execution of specific perceptual actions, such as moving closer to objects to acquire odour properties. Additional sensing modalities provides the spatial detection of objects and electronic olfaction then acquires the odour property which can be used for discrimination and recognition of the object being considered. We examine the problem of deciding when, how and where the e-nose should be activated by planning for active perception. We investigate the use of symbolic reasoning techniques in this context and consider the problem of integrating the information provided by the e-nose with both prior information and information from other sensors (e. g. , vision). Finally, experiments are performed on a mobile robot equipped with an e-nose together with a variety of sensors that can perform decision making tasks in realistic environments.

ECAI Conference 1998 Conference Paper

Delayed Effects of Actions

• Lars Karlsson
• Joakim Gustafsson
• Patrick Doherty 0001

IJCAI Conference 1997 Conference Paper

Reasoning with Incomplete Initial Information and Nondeterminism in Situation Calculus

• Lars Karlsson

Situation Calculus is arguably the most widely studied and used formalism for reasoning about action and change. The main reason for its popularity is the ability to reason about dif­ ferent action sequences as explicit objects. In particular, planning can be formulated as an existence problem. This paper shows how these properties break down when incomplete infor­ mation about the initial state and nondeterministic action effects are introduced, basically due to the fact that this incompleteness is not adequately manifested on the object level. A version of Situation Calculus is presented which adequately models the alternative ways the world can develop relative to a choice of ac­ tions.