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59
Fast Stochastic Motion Planning with Optimality Guarantees using Local Policy Reconfiguration
"... Abstract — This work presents a framework for fast reconfiguration of local control policies for a stochastic system to satisfy a high-level task specification. The motion of the system is abstracted to a class of uncertain Markov models known as bounded-parameter Markov decision processes (BMDPs). ..."
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Cited by 2 (2 self)
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Abstract — This work presents a framework for fast reconfiguration of local control policies for a stochastic system to satisfy a high-level task specification. The motion of the system is abstracted to a class of uncertain Markov models known as bounded-parameter Markov decision processes (BMDPs
Stochastic Extended LQR: Optimization-based Motion Planning Under Uncertainty
"... Abstract. We introduce a novel optimization-based motion planner, Stochastic Extended LQR (SELQR), which computes a trajectory and associated linear control policy with the objective of minimizing the ex-pected value of a user-defined cost function. SELQR applies to robotic systems that have stochas ..."
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Abstract. We introduce a novel optimization-based motion planner, Stochastic Extended LQR (SELQR), which computes a trajectory and associated linear control policy with the objective of minimizing the ex-pected value of a user-defined cost function. SELQR applies to robotic systems that have
Guaranteeing Communication Quality in Real World WSN Deployments
"... April 29, 2011Für UnsShe had never before seen a rabbit with either a waistcoat-pocket, or a watch to take out of it, and burning with curiosity, she ran across the field after it Lewis CarrollThe following document, written under the supervision of Dr. reviewed by: ..."
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April 29, 2011Für UnsShe had never before seen a rabbit with either a waistcoat-pocket, or a watch to take out of it, and burning with curiosity, she ran across the field after it Lewis CarrollThe following document, written under the supervision of Dr. reviewed by:
Smart resource reconfiguration by exploiting dynamics in perceptual tasks
- In Proceedings of International Conference on Robotics and Systems (IROS
, 2005
"... Abstract — In robot and sensor networks, one of the key challenges is to decide when and where to deploy sensory resources to gather information of optimal value. The problem is essentially one of planning, scheduling and controlling the sensors in the network to acquire data from an environment tha ..."
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Cited by 11 (3 self)
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ideas in a people tracking application using a network of multiple cameras. The task specification for our multi-camera network is one of allocating a camera pair that can best localize a human subject given the current context. The system automatically derives policies for switching between camera
Integrated motion planning and control for graceful balancing mobile robots
- The International Journal of Robotics Research, Special
, 2013
"... Abstract—This paper presents an integrated motion planning and control framework that enables balancing mobile robots to gracefully navigate human environments. A palette of controllers called motion policies is designed such that balancing mobile robots can achieve fast, graceful motions in small, ..."
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Cited by 1 (1 self)
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. The navigation tasks are achieved by planning in the space of these gracefully composable motion policies. In this work, Dijsktra’s algorithm is used to generate a single-goal optimal motion policy tree, and its variant is used to rapidly replan the optimal motion policy tree in the presence of dynamic obstacles
Optimal Temporal Logic Planning in Probabilistic Semantic Maps
"... Abstract—This paper considers robot motion planning under temporal logic constraints in probabilistic maps obtained by semantic simultaneous localization and mapping (SLAM). The uncertainty in a map distribution presents a great challenge for obtaining correctness guarantees with respect to the line ..."
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Abstract—This paper considers robot motion planning under temporal logic constraints in probabilistic maps obtained by semantic simultaneous localization and mapping (SLAM). The uncertainty in a map distribution presents a great challenge for obtaining correctness guarantees with respect
1Formal synthesis of optimal information-gathering policies
"... This paper considers the problem of informative path planning under temporal logic (TL) correctness constraints. For example, a robot deployed to a building after a natural disaster must explore the area and report possible locations of survivors with minimum uncertainty. The robot must satisfy the ..."
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the correctness requirement “Always avoid obstacles. Report data to rescuers at a data upload hub before exiting the scene. If a location with suspected fire is visited, investigate and report immediately. ” In this work, we map the constrained informative path planning problem to a stochastic optimal control
CERTIFICATE OF APPROVAL
, 2014
"... Treatment plan optimization for rotating-shield brachytherapy ..."
Scenario Generation and Reduction for Long-term and Short-term Power System Generation Planning under Uncertainties
"... ii ..."
A Formalism for Parallel Composition of Reactive and Deliberative Control Objectives for Mobile Robots
"... In this paper we introduce a methodology for closed loop motion planning which is able to reactively accommodate dynamic constraints, such as avoiding other robots, at run time without nesecatate a global replanning. The methodology is complete in the sense that it is guaranteed to produce a success ..."
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Cited by 3 (0 self)
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, the most common control policy of following the negated gradient is not the unique solution to the planning problem. We construct a parameterized set of acceptable control laws, and use the extra degrees of freedom in the parameter choice to satisfy the constraints by solving an optimization problem. Two
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