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Articles 1 - 10 of 10
Full-Text Articles in Physical Sciences and Mathematics
A Control Architecture Formulti-Modal Sensory Integration, Luiz M. G. Gonçalves, Roderic A. Grupen, Antonio A. F. Oliveira
A Control Architecture Formulti-Modal Sensory Integration, Luiz M. G. Gonçalves, Roderic A. Grupen, Antonio A. F. Oliveira
Roderic Grupen
This work describes the architecture of an integrated multi-modal sensory (vision and touch) computational system. We propose to use an approach based on robotics control theory that is motivated by biology and developmental psychology, in order to integrate the haptic and visual information processing. We show some results carried out in simulation and discuss the implementation of this system using a platform consisting on an articulated stereo-head and an arm, which is currently under development.
Constructing Skill Trees For Reinforcement Learning Agents From Demonstration Trajectories, George Konidaris, Scott Kuindersma, Andrew Barto, Roderic Grupen
Constructing Skill Trees For Reinforcement Learning Agents From Demonstration Trajectories, George Konidaris, Scott Kuindersma, Andrew Barto, Roderic Grupen
Roderic Grupen
We introduce CST, an algorithm for constructing skill trees from demonstration trajectories in continuous reinforcement learning domains. CST uses a change-point detection method to segment each trajectory into a skill chain by detecting a change of appropriate abstraction, or that a segment is too complex to model as a single skill. The skill chains from each trajectory are then merged to form a skill tree. We demonstrate that CST constructs an appropriate skill tree that can be further refined through learning in a challenging continuous domain, and that it can be used to segment demonstration trajectories on a mobile manipulator …
Learning From A Single Demonstration: Motion Planning With Skill Segmentation, Scott Kuindersma, George Konidaris, Roderic Grupen, Andrew Barto
Learning From A Single Demonstration: Motion Planning With Skill Segmentation, Scott Kuindersma, George Konidaris, Roderic Grupen, Andrew Barto
Roderic Grupen
We propose an approach to control learning from demonstration that first segments demonstration trajectories to identify subgoals to solve the overall task. Using this approach, we show that a mobile robot is able to solve a combined navigation and manipulation task robustly after observing only a single successful trajectory.
Mobile Manipulators For Assisted Living In Residential Settings, Patrick Deegan, Roderic Grupen, Allen Hanson, Emily Horrell, Shichao Ou, Edward Riseman, Shiraj Sen, Byan Thibodeau, Adam Williams, Dan Xie
Mobile Manipulators For Assisted Living In Residential Settings, Patrick Deegan, Roderic Grupen, Allen Hanson, Emily Horrell, Shichao Ou, Edward Riseman, Shiraj Sen, Byan Thibodeau, Adam Williams, Dan Xie
Roderic Grupen
We describe a methodology for creating new technologies for assisted living in residential environments. The number of eldercare clients is expected to grow dramatically over the next decade as the baby boom generation approaches 65 years of age. The UMass/Smith ASSIST framework aims to alleviate the strain on centralized medical providers and community services as their clientele grow, reduce the delays in service, support independent living, and therefore, improve the quality of life for the up-coming elder population. We propose a closed loop methodology wherein innovative technical systems are field tested in assisted care facilities and analyzed by social scientists …
Extracting User Intent In Mixed Initiative Teleoperator Control, Andrew H. Fagg, Michael Rosenstein, Robert Platt Jr., Roderic Grupen
Extracting User Intent In Mixed Initiative Teleoperator Control, Andrew H. Fagg, Michael Rosenstein, Robert Platt Jr., Roderic Grupen
Roderic Grupen
User fatigue is common with robot teleoperation interfaces. Mixed initiative control approaches attempt to reduce this fatigue by allowing control responsibility to be shared between the user and an intelligent control system. A critical challenge is how the user can communicate her intentions to the control system in an intuitive manner as possible. In the context of control of a humanoid robot, we propose an interface that uses the movement currently commanded by the user to assess the intended outcome. Specifically, given the observation of the motion of the teleoperated robot for a given period of time, we would like …
Scalability And Schedulability In Large, Coordinated, Distributed Robot Systems, John D. Sweeney, Huan Li, Roderic Grupen, Krithi Ramamritham
Scalability And Schedulability In Large, Coordinated, Distributed Robot Systems, John D. Sweeney, Huan Li, Roderic Grupen, Krithi Ramamritham
Roderic Grupen
Multiple, independent robot platforms promise significant advantage with respect to robustness and flexibility. However, coordination between otherwise independent robots requires the exchange of information; either implicitly (as in gestural communication), or explicitly (as in message passing in a communication network.) In either case, control processes resident on all coordinated peers must participate in the collective behavior. This paper evaluates the potential to scale such a coupled control framework to many participating individuals, where scalability is evaluated in terms of the schedulability of coupled distributed control processes. We examine how schedulability affects the scalability of a robot system, and discuss an …
A Service Paradigm For Reconfigurable Agents, Gary Holness, Deepak Karuppiah, Subramanya Uppala, Roderic Grupen, S. Chandu Ravela
A Service Paradigm For Reconfigurable Agents, Gary Holness, Deepak Karuppiah, Subramanya Uppala, Roderic Grupen, S. Chandu Ravela
Roderic Grupen
Applications of multiple processors embedded in the systems involved with entertainment, informatics, climate control, communication, transportation, and food preparation are already commonplace. A network of these embedded processors presents application development challenges since the state space grows exponentially as new devices attach to the network. The programming model for such systems will need to change if reliable systems are to be realized. By observing information about sensorimotor activity, such systems can gather information useful to programming the network. Through such interaction, a network can build hierarchies of shareable computational structures for representing various activities. This application domain presents additional challenges …
Dynamic Control Models As State Abstractions, Jefferson A. Coelho, Roderic Grupen
Dynamic Control Models As State Abstractions, Jefferson A. Coelho, Roderic Grupen
Roderic Grupen
This work proposes a methodology for the construction of state abstraction from a set of empirically derived models of system behavior. The idea is to treat the agent in its environment as a dynamical system and augment its observation space with contextual cues extracted empirically as the agent exercises each element out of the set of available control policies--the control bias. Contextual cues are provided by the correlation between dynamic features of the agent-environment interaction and agent performance. The resulting state abstraction (observations + context information) defines also a temporal abstraction, and offers interesting answers to some of the issues …
A Control Basis For Multilegged Walking, Manfred Huber, Willard S. Macdonald, Roderic Grupen
A Control Basis For Multilegged Walking, Manfred Huber, Willard S. Macdonald, Roderic Grupen
Roderic Grupen
This paper presents a distributed control approach to legged locomotion that constructs behavior on-line by activating combinations of reusable feedback control laws drawn from a control basis. Sequences of such controller activations result in flexible aperiodic step sequences based on local sensory information. Different tasks are achieved by varying the composition functions over the same basis controllers, rather than by geometric planning of leg placements or the design of new task-specific behaviors. In addition, the device-independent nature of the control basis allows its generalization not only over task domains, but also over different hardware platforms. To show the applicability of …
Robust Reinforcement Learning In Motion Planning, Satinder P. Singh, Andrew G. Barto, Roderic Grupen, Christopher Connolly
Robust Reinforcement Learning In Motion Planning, Satinder P. Singh, Andrew G. Barto, Roderic Grupen, Christopher Connolly
Roderic Grupen
While exploring to find better solutions, an agent performing on-line reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, or even catastrophic, results, often modeled in terms of reaching 'failure' states of the agent's environment. This paper presents a method that uses domain knowledge to reduce the number of failures during exploration. This method formulates the set of actions from which the RL agent composes a control policy to ensure that exploration is conducted in a policy space that excludes most of the unacceptable policies. The resulting action set has a more abstract …