Grandpa Hates Robots - Interaction Constraints for Planning in Inhabited Environments

Köckemann, Uwe; Pecora, Federico; Karlsson, Lars

doi:10.1609/aaai.v28i1.9032

Cited by 8 publications

(5 citation statements)

References 22 publications

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“…Moreover, generally, they produce explicitly coordinated, shared HR plans that are legible and acceptable by humans -they are assumed to be controllable in some sense, such that the techniques rely more on the replanning aspect. In [12], [21], the objectives of the humans around robots define robots' existence and contingent tasks, e.g., do not use the vacuum cleaner when humans go to sleep. However, more importantly, they do not have an explicitly shared task to achieve as a team.…”

Section: Related Work A) Theory Of Mind In Hrcmentioning

confidence: 99%

Models and Algorithms for Human-Aware Task Planning with Integrated Theory of Mind

Favier,

Shekhar,

Alami

2023

2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)

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It is essential for a collaborative robot to consider the Theory of Mind (ToM) when interacting with humans. Indeed, performing an action in the absence of another agent may create false beliefs like in the well-known Sally & Anne Task [1]. The robot should be able to detect, react to, and even anticipate false beliefs of other agents with a detrimental impact on the task to achieve. Currently, ToM is mainly used to control the task execution and resolve in a reactive way the detrimental false beliefs. Some works introduce ToM at the planning level by considering distinct beliefs, and we are in this context. This work proposes an extension of an existing human-aware task planner and effectively allows the robot to anticipate a false human belief ensuring a smooth collaboration through an implicitly coordinated plan. First, we propose to capture the observability properties of the environment in the state description using two observability types and the notion of co-presence. They allow us to maintain distinct agent beliefs by reasoning directly on what agents can observe through specifically modeled Situation Assessment processes, instead of reasoning of action effects. Then, thanks to the better estimated human beliefs, we can predict if a false belief with adverse impact will occur. If that is the case then, first, the robot's plan can be to communicate minimally and proactively. Second, if this false belief is due to a non-observed robot action, the robot's plan can be to postpone this action until it can be observed by the human, avoiding the creation of the false belief. We implemented our new conceptual approach, discuss its effectiveness qualitatively, and show experimental results on three novel domains.

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Section: Related Work A) Theory Of Mind In Hrcmentioning

confidence: 99%

Models and Algorithms for Human-Aware Task Planning with Integrated Theory of Mind

Favier,

Shekhar,

Alami

2023

2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)

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“…As we mentioned before, in the case of motion planning, there is often no such distinction. Even in the case of task planning -for example, in "human-aware" planning where an agent decides not to vacuum while the elderly are asleep (Köckemann, Pecora, and Karlsson 2014) -sometimes it may be hard to identify where exactly the constraints lie, with preferences ("I don't want vacuuming while I am asleep") or expectations ("I don't expect the agent to be designed to vacuum at odd hours"). Ultimately this distinction might not make a difference algorithmically.…”

Section: On Preferences Versus Expectationsmentioning

confidence: 99%

Explicability? Legibility? Predictability? Transparency? Privacy? Security? The Emerging Landscape of Interpretable Agent Behavior

Chakraborti

Kulkarni

Sreedharan

et al. 2021

ICAPS

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There has been significant interest of late in generating behavior of agents that is interpretable to the human (observer) in the loop. However, the work in this area has typically lacked coherence on the topic, with proposed solutions for “explicable”, “legible”, “predictable” and “transparent” planning with overlapping, and sometimes conflicting, semantics all aimed at some notion of understanding what intentions the observer will ascribe to an agent by observing its behavior. This is also true for the recent works on “security” and “privacy” of plans which are also trying to answer the same question, but from the opposite point of view – i.e. when the agent is trying to hide instead of reveal its intentions. This paper attempts to provide a workable taxonomy of relevant concepts in this exciting and emerging field of inquiry.

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“…There are many approaches where planning problems are encoded into SAT problems or CSPs (Kautz, Selman, and Hoffmann 2006;Kambhampati 2000). Constraint-based planning as described by (Köckemann, Pecora, and Karlsson 2014;Köckemann 2016) is instead an approach to planning that models different aspects of a domain with different types of constraints. This approach was used to provide solutions for several challenges of human-aware planning.…”

Section: Related Researchmentioning

confidence: 99%

“…If for any CDB Φ we have ic ∈ Φ and Φ ∪ Condition can be satisfied, at least one r ∈ Resolvers(ic) must be satisfiable. Previously, ICs were used to constrain the interaction with humans (Köckemann, Pecora, and Karlsson 2014). Here we use them to add goals when certain information links are used (only required by our second approach).…”

Section: Constraint-based Planningmentioning

confidence: 99%

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Configuration Planning with Temporal Constraints

Köckemann

Karlsson

2017

AAAI

Self Cite

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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.

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Grandpa Hates Robots - Interaction Constraints for Planning in Inhabited Environments

Cited by 8 publications

References 22 publications

Models and Algorithms for Human-Aware Task Planning with Integrated Theory of Mind

Models and Algorithms for Human-Aware Task Planning with Integrated Theory of Mind

Explicability? Legibility? Predictability? Transparency? Privacy? Security? The Emerging Landscape of Interpretable Agent Behavior

Configuration Planning with Temporal Constraints

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