Sachin Patil

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We present a new approach to motion planning under sensing and motion uncertainty by computing a locally optimal solution to a continuous partially observable Markov decision process (POMDP). Our approach represent beliefs (the distributions of the robot’s state estimate) by Gaussian distributions and is applicable to robot systems with non-linear dynamics(More)
We present a novel approach for interactive navigation and planning of multiple agents in crowded scenes with moving obstacles. Our formulation uses a precomputed roadmap that provides macroscopic, global connectivity for wayfinding and combines it with fast and localized navigation for each agent. At runtime, each agent senses the environment independently(More)
We present a new optimization-based approach for robotic motion planning among obstacles. Like CHOMP (Covariant Hamiltonian Optimization for Motion Planning), our algorithm can be used to find collision-free trajectories from naïve, straight-line initializations that might be in collision. At the core of our approach are (a) a sequential convex optimization(More)
This paper presents empirical results to support the use of vibrotactile cues as a means of improving user performance on a spatial task. In a building-clearing exercise, directional vibrotactile cues were employed to alert subjects to areas of the building that they had not yet cleared, but were currently exposed to. Compared with performing the task(More)
The Cloud infrastructure and its extensive set of Internet-accessible resources has potential to provide significant benefits to robots and automation systems. We consider robots and automation systems that rely on data or code from a network to support their operation, i.e., where not all sensing, computation, and memory is integrated into a standalone(More)
INTRODUCTION Neurofibromatosis 1 is a tumor predisposition genetic syndrome with autosomal dominant inheritance and virtually 100% penetrance by the age of 5 years. NF1 results from a loss-of-function mutation in the NF1 gene, resulting in decreased levels of neurofibromin in the cell. Neurofibromin is a negative regulator of various intracellular signaling(More)
Bevel-tip steerable needles for minimally invasive medical procedures can be used to reach clinical targets that are behind sensitive or impenetrable areas and are inaccessible to straight, rigid needles. We present a fast algorithm that can compute motion plans for steerable needles to reach targets in complex, 3D environments with obstacles at interactive(More)
Belief space planning provides a principled framework to compute motion plans that explicitly gather information from sensing, as necessary, to reduce uncertainty about the robot and the environment. We consider the problem of planning in Gaussian belief spaces, which are parameterized in terms of mean states and covariances describing the uncertainty. In(More)
We propose an information-theoretic planning approach that enables mobile robots to autonomously construct dense 3D maps in a computationally efficient manner. Inspired by prior work, we accomplish this task by formulating an information-theoretic objective function based on CauchySchwarz quadratic mutual information (CSQMI) that guides robots to obtain(More)
We present an approach to motion planning under motion and sensing uncertainty, formally described as a continuous partially-observable Markov decision process (POMDP). Our approach is designed for non-linear dynamics and observation models, and follows the general POMDP solution framework in which we represent beliefs by Gaussian distributions, approximate(More)