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Intelligent robots and machines are becoming pervasive in human populated environments. A desirable capability of these agents is to respond to goal-oriented commands by autonomously constructing task plans. However, such autonomy can add significant cognitive load and potentially introduce safety risks to humans when agents behave in unexpected ways. Hence, for such agents to be helpful, one important...
There has been a great deal of work on learning new robot skills, but very little consideration of how these newly acquired skills can be integrated into an overall intelligent system. A key aspect of such a system is compositionality: newly learned abilities have to be characterized in a form that will allow them to be flexibly combined with existing abilities, affording a (good!) combinatorial explosion...
We propose a mathematical framework for synthesizing motion plans for multi-agent systems that fulfill complex, high-level and formal local specifications in the presence of inter-agent communication. The proposed synthesis framework consists of desired motion specifications in temporal logic (STL) formulas and a local motion controller that ensures the underlying agent not only to accomplish the...
The paper addresses path planning for a redundant robot arm that is maneuvering in confined spaces, where neither an explicit model nor external perception of the possibly frequently changing environment is available. Our approach is rather solely based on data from kinesthetic demonstrations of feasible configurations provided by a user. The key challenge is to create a graph-based representation...
Service and assistance robots that must move in human environment must address the difficult issue of navigating in dynamic environments. As it has been shown in previous works, in such situations the robots can take advantage of the motion of persons by following them, managing to move together with humans in difficult situations. In those circumstances, the problem to be solved is how to choose...
An unsupervised attention-path planning algorithm is proposed and applied to large unknown area classification with small field-of-view cameras. Attention-path planning is formulated as the sequential feature selection problem that greedily finds a sequence of attentions to obtain more informative observations, yielding faster training and higher accuracies. In order to find the near-optimal attention-path,...
We present a motion planning algorithm for dynamic vehicles navigating through unknown environments. We focus on the scenario in which a fast-moving car attempts to navigate from a start location to a set of goal coordinates in minimum time with no prior information about the environment, building a map in real time from onboard sensor data. Whereas existing planners for exploration confine themselves...
While collision-free navigation could be done using existing rule-based approaches, it becomes more attractive to use learning from demonstration (LfD) approaches to ease the burden of tedious rule designing and parameter tuning procedures. In addition, in the freezing robot problem, once the environment surpasses a certain level of complexity, there may be no sufficient space for a robot to navigate...
The ability to plan their own motions and to reliably execute them is an important precondition for autonomous robots. In this paper, we consider the problem of planning the motion of a mobile manipulation robot in the presence of deformable objects. Our approach combines probabilistic roadmap planning with a physical deformation simulation system. Since the physical deformation simulation is computationally...
In this paper, we discuss a strategy for the adaptation of the “difficulty level” in games intended to include motor planning during robotic rehabilitation. We consider concurrently the motivation of the user and his/her performance in a Pong game. User motivation is classified in three levels (not motivated, well motivated and overloaded). User performance is measured as a combination of knowledge...
Motor deficits in the growing population of stroke survivors continue to strain global healthcare capacities. The use of telerehabilitation to address this need has been discussed for over a decade without a clear consensus on development strategy or a clear market success. In this paper, the cyclic and iterative phases of the Planning, Execution, Assessment (PLEXAS) rehabilitation cycle are discussed,...
Planning techniques recorded a significant progress during recent years. However, many planning problems remain still hard even for modern planners. One of the most promising approaches is gathering additional knowledge by using learning techniques. Well known sort of knowledge - macro-operators, formalized like 'normal' planning operators, represent a sequence of primitive planning operators. The...
At the heart of multi-robot task allocation lies the ability to compare multiple options in order to select the best. In some domains this utility evaluation is not straightforward, for example due to complex and unmodeled underlying dynamics or an adversary in the environment. Explicitly modeling these extrinsic influences well enough so that they can be accounted for in utility computation (and...
In this work, we present a formulation of an evacuation planning problem that is inspired by motion planning and describe an integrated behavioral agent-based and roadmap-based motion planning approach to solve it. Our formulation allows users to test the effect on evacuation of a number of different environmental factors. One of our main focuses is to provide a mechanism to investigate how the interaction...
Trajectory planning of robot is to control the robot in order to accurately follow the target track. And the target trajectory is always high-order and nonlinear. But RBF neural network can be achieved from the input to the output of arbitrary nonlinear mapping, through network learning and training to achieve the nonlinear function. This paper establishes a RBF neural network model firstly, and carries...
Since planning environments are complex and no single planner exists that is best for all problems, much work has been done to explore methods for selecting where and when to apply particular planners. However, these two questions have been difficult to answer, even when adaptive methods meant to facilitate a solution are applied. For example, adaptive solutions such as setting learning rates, hand-classifying...
This paper addresses the problem of generating autonomously an optimal control action sequence for robotic autonomous unmanned vehicles based on adaptive critic designs (ACDs) for their use in autonomous agriculture vehicles, in the context of precision agriculture. The main objective is to design autonomously an optimal controller that steers the center of the vehicle through a number of waypoints...
The art of computer-based game production is an aspiring goal and a challenging task. It involves many different activities, expertise and skills into many different areas such as: game theory, programming skills, multimedia, 2D/3D graphics and animation, sound engineering, story writing, project design and management, physics, logic design, interface programming, artificial intelligence (AI) and...
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