20 research outputs found
Contact-Implicit Trajectory Optimization Based on a Variable Smooth Contact Model and Successive Convexification
In this paper, we propose a contact-implicit trajectory optimization (CITO)
method based on a variable smooth contact model (VSCM) and successive
convexification (SCvx). The VSCM facilitates the convergence of gradient-based
optimization without compromising physical fidelity. On the other hand, the
proposed SCvx-based approach combines the advantages of direct and shooting
methods for CITO. For evaluations, we consider non-prehensile manipulation
tasks. The proposed method is compared to a version based on iterative linear
quadratic regulator (iLQR) on a planar example. The results demonstrate that
both methods can find physically-consistent motions that complete the tasks
without a meaningful initial guess owing to the VSCM. The proposed SCvx-based
method outperforms the iLQR-based method in terms of convergence, computation
time, and the quality of motions found. Finally, the proposed SCvx-based method
is tested on a standard robot platform and shown to perform efficiently for a
real-world application.Comment: Accepted for publication in ICRA 201
Autonomous Robot Navigation with Rich Information Mapping in Nuclear Storage Environments
This paper presents our approach to develop a method for an unmanned ground
vehicle (UGV) to perform inspection tasks in nuclear environments using rich
information maps. To reduce inspectors' exposure to elevated radiation levels,
an autonomous navigation framework for the UGV has been developed to perform
routine inspections such as counting containers, recording their ID tags and
performing gamma measurements on some of them. In order to achieve autonomy, a
rich information map is generated which includes not only the 2D global cost
map consisting of obstacle locations for path planning, but also the location
and orientation information for the objects of interest from the inspector's
perspective. The UGV's autonomy framework utilizes this information to
prioritize locations to navigate to perform the inspections. In this paper, we
present our method of generating this rich information map, originally
developed to meet the requirements of the International Atomic Energy Agency
(IAEA) Robotics Challenge. We demonstrate the performance of our method in a
simulated testbed environment containing uranium hexafluoride (UF6) storage
container mock ups
Path planning for socially-aware humanoid robots
Designing efficient autonomous navigation systems for mobile robots involves consideration of the robotĂs environment while arriving at a systems architecture that trades off multiple constraints. We have architected a navigation framework for socially-aware autonomous robot navigation, using only the on-board computing resources. Our goal is to foster the development of several important service robotics applications using this platform. Our framework allows a robot to autonomously navigate in indoor environments while accounting for people (i.e., estimating the path of all individuals in the environment), respecting each individualĂs private space.
In our design, we can leverage a wide number of sensors for navigation, including cameras, 2D and 3D scanners, and motion trackers. When designing our sensor system, we have considered that mobile robots have limited resources (i.e., power and computation) and that some sensors are costlier than others (e.g., cameras and 3D scanners stream data at high rates), requiring intensive computation to provide useful insight for real-time navigation. We tradeoff between accuracy, responsiveness, and power, and choose a Hokuyo UST-20LX 2D laser scanner for robot localization, obstacle detection and people tracking. We use an MPU-6050 for motion tracking.
Our navigation framework features a low-power sensor system (< 5W) tailored for improved battery life in robotic applications while providing sufficient accuracy. We have completed a prototype for a Human Support Robot using the available onboard computing devices, requiring less than 60W to run. We estimate we can obtain similar performance, while reducing power by ~60%, utilizing low-power high-performance accelerator hardware and parallelized software.Universidad de Málaga. Campus de Excelencia Internacional AndalucĂa Tec
A Comparative Analysis of Contact Models in Trajectory Optimization for Manipulation
In this paper, we analyze the effects of contact models on contact-implicit
trajectory optimization for manipulation. We consider three different
approaches: (1) a contact model that is based on complementarity constraints,
(2) a smooth contact model, and our proposed method (3) a variable smooth
contact model. We compare these models in simulation in terms of physical
accuracy, quality of motions, and computation time. In each case, the
optimization process is initialized by setting all torque variables to zero,
namely, without a meaningful initial guess. For simulations, we consider a
pushing task with varying complexity for a 7 degrees-of-freedom robot arm. Our
results demonstrate that the optimization based on the proposed variable smooth
contact model provides a good trade-off between the physical fidelity and
quality of motions at the cost of increased computation time.Comment: 6 pages, 7 figures, 4 tables, IROS 2018 camera-ready versio
Robotics Enabled In-Home Environment Screening for Fall Risks
Our overarching goal is to investigate, design, create and validate the fundamental scientific and engineering framework for intelligent, networked mobile robots to semi-autonomously perform environmental fall risk assessment in the home. Motivated by the facts that (1) aging in place improves the overall health and well-being of individuals, (2) falls are the leading cause of mortality in older adults, (3) home environmental fall risk assessment is an effective preventive strategy, and (4) extreme costs and shortage of trained personnel are huge barriers for effective and efficient delivery of fall risk home assessments by health care providers, we are iteratively developing user-centric designs for a new class of robotic systems that can be assembled easily and cost-effectively to detect environmental hazards and, as a result, preventively and proactively minimize falls in the home. The tight integration of the research thrusts in robot design and control, task and motion planning under uncertainty, and human-on-the-mesh control of networked robots is aimed at advancing the theory and practice of robotics and lead to the demonstration of innovative approaches to transform healthcare delivery with a focus on wellbeing. In this poster presentation, we will present our preliminary results from developing this framework. We present the communication and control framework for a semi-autonomous mobile robot that can be controlled over an internet connection via a web interface. We will discuss the opportunities and challenges associated with a human-robot team completing the HEROS (http://www.temple.edu/older_adult/) environment safety checklist. Our preliminary results demonstrate that this technology can be helpful to effectively prevent the in-home falls among elderly