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51
Temporal-Logic-Based Reactive Mission and Motion Planning
, 2009
"... This paper provides a framework to automatically generate a hybrid controller that guarantees that the robot can achieve its task when a robot model, a class of admissible environments, and a high-level task or behavior for the robot are provided. The desired task specifications, which are expresse ..."
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Cited by 58 (11 self)
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This paper provides a framework to automatically generate a hybrid controller that guarantees that the robot can achieve its task when a robot model, a class of admissible environments, and a high-level task or behavior for the robot are provided. The desired task specifications, which are expressed in a fragment of linear temporal logic (LTL), can capture complex robot behaviors such as search and rescue, coverage, and collision avoidance. In addition, our framework explicitly captures sensor specifications that depend on the environment with which the robot is interacting, which results in a novel paradigm for sensor-based temporal-logic-motion planning. As one robot is part of the environment of another robot, our sensor-based framework very naturally captures multirobot specifications in a decentralized manner. Our computational approach is based on first creating discrete controllers satisfying specific LTL formulas. If feasible, the discrete controller is then used to guide the sensor-based composition of continuous controllers, which results in a hybrid controller satisfying the high-level specification but only if the environment is admissible.
Sampling-based motion planning with temporal goals
- IN IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2010. PROCEEDINGS
, 2010
"... This paper presents a geometry-based, multilayered synergistic approach to solve motion planning problems for mobile robots involving temporal goals. The temporal goals are described over subsets of the workspace (called propositions) using temporal logic. A multi-layered synergistic framework has ..."
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Cited by 49 (6 self)
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This paper presents a geometry-based, multilayered synergistic approach to solve motion planning problems for mobile robots involving temporal goals. The temporal goals are described over subsets of the workspace (called propositions) using temporal logic. A multi-layered synergistic framework has been proposed recently for solving planning problems involving significant discrete structure. In this framework, a high-level planner uses a discrete abstraction of the system and the exploration information to suggest feasible high-level plans. A low-level sampling-based planner uses the physical model of the system, and the suggested high-level plans, to explore the state-space for feasible solutions. In this paper, we advocate the use of geometry within the above framework to solve motion planning problems involving temporal goals. We present a technique to construct the discrete abstraction using the geometry of the obstacles and the propositions defined over the workspace. Furthermore, we show through experiments that the use of geometry results in significant computational speedups compared to previous work. Traces corresponding to trajectories of the system are defined employing the sampling interval used by the low-level algorithm. The applicability of the approach is shown for second-order nonlinear robot models in challenging workspace environments with obstacles, and for a variety of temporal logic specifications.
Talking to Computers
- Scientific American
, 2003
"... Our broad claim is that time-sensitive metar- easoning can enhance the ability of natural language HCI systems to converse with human interlocutors, by giving these systems both the time-awareness and meta-linguistic skills (in- cluding especially the ability to recognize and repair dialog problems, ..."
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Cited by 43 (11 self)
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Our broad claim is that time-sensitive metar- easoning can enhance the ability of natural language HCI systems to converse with human interlocutors, by giving these systems both the time-awareness and meta-linguistic skills (in- cluding especially the ability to recognize and repair dialog problems, by learning if need be) which appear to be necessary for free, flexible, and natural conversation. We illustrate this en- hancement with a description of our ongoing work in cooperative natural language HCI sys- tems.
Optimal path planning for surveillance with temporal-logic constraints
- The International Journal of Robotics Research
"... In this paper we present a method for automatically generating optimal robot paths satisfying high level mission specifications. The motion of the robot in the environment is modeled as a weighted transition system. The mission is specified by an arbitrary linear temporal logic (LTL) formula over pr ..."
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Cited by 22 (7 self)
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In this paper we present a method for automatically generating optimal robot paths satisfying high level mission specifications. The motion of the robot in the environment is modeled as a weighted transition system. The mission is specified by an arbitrary linear temporal logic (LTL) formula over propositions satisfied at the regions of a partitioned environment. The mission specification contains an optimizing proposition which must be repeatedly satisfied. The cost function that we seek to minimize is the maximum time between satisfying instances of the optimizing proposition. For every environment model, and for every formula, our method computes a robot path which minimizes the cost function. The problem is motivated by applications in robotic monitoring and data gathering. In this setting, the optimizing proposition is satisfied at all locations where data can be uploaded, and the LTL formula specifies a complex data collection mission. Our method utilizes Büchi automata to produce an automaton (which can be thought of as a graph) whose runs satisfy the temporal logic specification. We then present a graph algorithm which computes a run corresponding to the optimal robot path. We present an implementation for a robot performing data collection in a road network platform. 1
Temporal Logic-based Reactive Mission and Motion Planning
"... Given a robot model, a class of admissible environments and a high level task or behavior for the robot, this paper provides a framework for automatically generating a hybrid controller that guarantees the robot can achieve its task. The desired task specifications, expressed in a fragment of linea ..."
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Cited by 19 (0 self)
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Given a robot model, a class of admissible environments and a high level task or behavior for the robot, this paper provides a framework for automatically generating a hybrid controller that guarantees the robot can achieve its task. The desired task specifications, expressed in a fragment of linear temporal logic, can capture complex robot behaviors such as search and rescue, coverage, and collision avoidance. In addition, our framework explicitly captures sensor specifications that depend on the environment with which the robot is interacting, resulting in a novel paradigm for sensor-based temporal logic motion planning. As one robot is part of the environment of another robot, our sensor-based framework very naturally captures multi-robot specifications in a decentralized manner. Our computational approach is based on first creating discrete controllers satisfying specific Linear Temporal Logic formulas. If feasible, the discrete controller is then used to guide the sensor-based composition of continuous controllers, resulting in a hybrid controller satisfying the high-level specification, but only if the environment is admissible.
Iterative Temporal Motion Planning for Hybrid Systems in Partially Unknown Environments
"... This paper considers the problem of motion planning for a hybrid robotic system with complex and nonlinear dynamics in a partially unknown environment given a temporal logic specification. We employ a multi-layered synergistic framework that can deal with general robot dynamics and combine it with a ..."
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Cited by 13 (4 self)
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This paper considers the problem of motion planning for a hybrid robotic system with complex and nonlinear dynamics in a partially unknown environment given a temporal logic specification. We employ a multi-layered synergistic framework that can deal with general robot dynamics and combine it with an iterative planning strategy. Our work allows us to deal with the unknown environmental restrictions only when they are discovered and without the need to repeat the computation that is related to the temporal logic specification. In addition, we define a metric for satisfaction of a specification. We use this metric to plan a trajectory that satisfies the specification as closely as possible in cases in which the discovered constraint in the environment renders the specification unsatisfiable. We demonstrate the efficacy of our framework on a simulation of a hybrid second-order car-like robot moving in an office environment with unknown obstacles. The results show that our framework is successful in generating a trajectory whose satisfaction measure of the specification is optimal. They also show that, when new obstacles are discovered, the reinitialization of our framework is computationally inexpensive.
Revising temporal logic specifications for motion planning
- In IEEE International Conference on Robotics and Automation
, 2011
"... Abstract — In this paper, we introduce the problem of auto-matic formula revision for Linear Temporal Logic (LTL) motion planning specifications. Namely, if a specification cannot be satisfied on a particular environment, our framework returns information to the user regarding (i) why the specificat ..."
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Cited by 13 (2 self)
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Abstract — In this paper, we introduce the problem of auto-matic formula revision for Linear Temporal Logic (LTL) motion planning specifications. Namely, if a specification cannot be satisfied on a particular environment, our framework returns information to the user regarding (i) why the specification cannot be satisfied and (ii) how the specification can be modified so it can become satisfiable. This work contributes towards rendering temporal logic motion planning frameworks more user friendly by providing feedback to the user when the LTL planning phase fails. I.
Motion planning with hybrid dynamics and temporal goals
- In Decision and Control, IEEE Conf. on
, 2010
"... Abstract — In this paper, we consider the problem of motion planning for mobile robots with nonlinear hybrid dynamics, and high-level temporal goals. We use a multi-layered synergistic framework that has been proposed recently for solving planning problems involving hybrid systems and high-level tem ..."
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Cited by 11 (4 self)
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Abstract — In this paper, we consider the problem of motion planning for mobile robots with nonlinear hybrid dynamics, and high-level temporal goals. We use a multi-layered synergistic framework that has been proposed recently for solving planning problems involving hybrid systems and high-level temporal goals. In that framework, a high-level planner employs a userdefined discrete abstraction of the hybrid system as well as exploration information to suggest high-level plans. A low-level sampling-based planner uses the dynamics of the hybrid system and the suggested high-level plans to explore the state-space for feasible solutions. In previous work, we have proposed a geometry-based approach for the construction of the discrete abstraction for the case when the robot is modeled as a continuous system. Here, we extend the approach for the construction of the discrete abstraction to the case when the robot is modeled as nonlinear hybrid system. To use the resulting abstraction more efficiently, we also propose a lazysearch approach for high-level planning that reduces the size of the search space by reusing previously constructed highlevel plans for initializing the search. Our proposed techniques result in computational speedups of close to 10 times over other possible approaches for second-order nonlinear hybrid robot models in challenging workspace environments with obstacles and for a variety of temporal logic specifications. I.
Mobile manipulation: Encoding motion planning options using task motion multigraphs
- In IEEE International Conference on Robotics and Automation
, 2011
"... Abstract — This paper introduces the concept of a task motion multigraph, a data structure that can be used to reveal a difficulty specific to mobile manipulation: the possibility of planning in different state spaces in order to achieve the same goal. The different options reflect the mobile manipu ..."
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Cited by 11 (4 self)
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Abstract — This paper introduces the concept of a task motion multigraph, a data structure that can be used to reveal a difficulty specific to mobile manipulation: the possibility of planning in different state spaces in order to achieve the same goal. The different options reflect the mobile manipulator’s ability to use different hardware components to perform a required task. For instance, a humanoid robot can open a door with its left arm or with its right arm. Thus, motion planning can be performed in the left arm’s state space or in the right arm’s state space. Given the specification of a task, it is shown how to encode the available motion planning options in a task motion multigraph. An algorithm that computes sequences of motion plans for mobile manipulators using the newly introduced notion is presented and evaluated. The algorithm makes use of information from the task motion multigraph to prioritize the spaces for which motion plans are computed. Experimental results show that reduced planning times can be obtained when considering the available planning options. I.
On the Revision Problem of Specification Automata
"... Abstract — One of the important challenges in robotics is the automatic synthesis of provably correct controllers from high level specifications. One class of such algorithms operates in two steps: (i) high level discrete controller synthesis and (ii) low level continuous controller synthesis. In th ..."
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Cited by 10 (5 self)
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Abstract — One of the important challenges in robotics is the automatic synthesis of provably correct controllers from high level specifications. One class of such algorithms operates in two steps: (i) high level discrete controller synthesis and (ii) low level continuous controller synthesis. In this class of algorithms, when phase (i) fails, then it is desirable to provide feedback to the designer in the form of revised specifications that can be achieved by the system. In this paper, we address the minimal revision problem for specification automata. That is, we construct automata specifications that are as “close ” as possible to the initial user intent, by removing the minimum number of constraints from the specification that cannot be satisfied. We prove that the problem is computationally hard and we encode it as a satisfiability problem. Then, the minimal revision problem can be solved by utilizing efficient SAT solvers. I.
