48 research outputs found
Learning Controllers for Continuum Soft Manipulators: Impact of Modeling and Looming Challenges
No full textLimit-point buckling analyses using solid, shell and solid–shell elements
No full textIn this paper, the recently-developed solid-shell element SHB8PS is used for the analysis of a representative set of popular limit-point buckling benchmark problems. For this purpose, the element has been implemented in Abaqus/Standard finite element software and the modified Riks method was employed as an efficient path-following strategy. For the. benchmark problems tested, the new element shows better performance compared to solid elements and often performs as well as state-of-the-art shell elements. In contrast to shell elements, it allows for the accurate prescription of boundary conditions as applied to the actual edges of the structure.Agence Nationale de la Recherche, France (ANR-005-RNMP-007
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The BYU Mars Rover and the 2022 University Rover Challenge
No full textOur team designed, developed, and implemented a rover capable of autonomous and manual remote operation for the purpose of competing in the University Rover Challenge (URC). In this paper, we present and discuss the critical role that telemetry systems play in facilitating communication between sensors onboard the rover and the base-station computer. The rover features multiple sub-systems such as a science module, cameras, and other components that utilize various modern communication techniques to enable a fully functional system.International Foundation for TelemeteringProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit https://telemetry.org/contact-us/ if you have questions about items in this collection
Mass digitization system
No full textA mass digitization system may include a work Surface rotat ably coupled to a Support structure, and a motor coupled to the work Surface to selectively rotate the work Surface. An imag ing station may be positioned proximate the work Surface to capture digital images of items on a receiving Surface of the work surface. The motor may rotate the work surface and the imaging station may include an imaging device to capture images of items on the receiving Surface as the items are positioned in the image capture area of the imaging device
Real-time evolutionary model predictive control using a graphics processing unit
No full textWith humanoid robots becoming more complex and operating in un-modeled or human environments, there is a growing need for control methods that are scalable and robust, while still maintaining compliance for safety reasons. Model Predictive Control (MPC) is an optimal control method which has proven robust to modeling error and disturbances. However, it can be difficult to implement for high degree of freedom (DoF) systems due to the optimization problem that must be solved. While evolutionary algorithms have proven effective for complex large-scale optimization problems, they have not been formulated to find solutions quickly enough for use with MPC. This work details the implementation of a parallelized evolutionary MPC (EMPC) algorithm which is able to run in real-time through the use of a Graphics Processing Unit (GPU). This parallelization is accomplished by simulating candidate control input trajectories in parallel on the GPU. We show that this framework is more flexible in terms of cost function definition than traditional MPC and that it shows promise for finding solutions for high DoF systems
Automated Tracking and Estimation for Control of Non-rigid Cloth
No full textThis report is a summary of research conducted on cloth tracking for automated textile manufacturing during a two semester long research course at Georgia Tech. This work was completed in 2009. Advances in current sensing technology such as the Microsoft Kinect would now allow me to relax certain assumptions and generally improve the tracking performance. This is because a major part of my approach described in this paper was to track features in a 2D image and use these to estimate the cloth deformation. Innovations such as the Kinect would improve estimation due to the automatic depth information obtained when tracking 2D pixel locations. Additionally, higher resolution camera images would probably give better quality feature tracking. However, although I would use different technology now to implement this tracker, the algorithm described and implemented in this paper is still a viable approach which is why I am publishing this as a tech report for reference. In addition, although the related work is a bit exhaustive, it will be useful to a reader who is new to methods for tracking and estimation as well as modeling of cloth
Estimating Joint Configuration for Soft Robots
No full textSoft robotics are still a relatively new technology. As seen in Figure 1, they are made entirely from compliant materials that use pressurized fluid for both structure and actuation. These robots have great potential in the world of robotics. Soft robots can excel in many areas where rigid robots fall short due to their incredible compliance and low inertia. As soft robotic technologies develop, robots will be much less limited in the scope of what they can do without risk of human injury. They will be able to do tasks working more closely with humans in current industries, and be able to enter new industries
Fast reaching in clutter while regulating forces using model predictive control
No full textMoving a robot arm quickly in cluttered and unmodeled workspaces can be difficult because of the inherent risk of high impact forces. Additionally, compliance by itself is not enough to limit contact forces due to multi-contact phenomena (jamming, etc.). The work in this paper extends our previous research on manipulation in cluttered environments by explicitly modeling robot arm dynamics and using model predictive control (MPC) with whole-arm tactile sensing to improve the speed and force control. We first derive discrete-time dynamic equations of motion that we use for MPC. Then we formulate a multi-time step model predictive controller that uses this dynamic model. These changes allow us to control contact forces while increasing overall end effector speed. We also describe a constraint that regulates joint velocities in order to mitigate unexpected impact forces while reaching to a goal. We present results using tests from a simulated three link planar arm that is representative of the kinematics and mass of an average male\u27s torso, shoulder and elbow joints reaching in high and low clutter scenarios. These results show that our controller allows the arm to reach a goal up to twice as fast as our previous work, while still controlling the contact forces to be near a user-defined threshold
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BYU MARS ROVER TELEMETRY IN THE 2025 UNIVERSITY ROVER CHALLENGE
No full textAs part of a senior-level capstone design course, our team designed, developed, and built a planetary rover for the University Rover Challenge (URC), capable of autonomous and manual remote operation. This paper presents and discusses the role of telemetry systems in facilitating communication between sensors onboard the rover and the base-station computer. The rover featured several critical subsystems, including a wirelessly-controlled differential drive system, localization, navigation, and perception solutions, a science module, and a 6-DOF robotic arm. These subsystems shared information with the base-station computer over a long-range antenna using ROS 1 and ROS 2. Overall, we focused on implementing robust and reliable communication approaches to ensure low-latency operation, given the URC’s long-range, bandwidth-limited connection requirements.International Foundation for TelemeteringProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit https://telemetry.org/contact/ if you have questions about items in this collection
Model predictive control for fast reaching in clutter
No full textA key challenge for haptically reaching in dense clutter is the frequent contact that can occur between the robot’s arm and the environment. We have previously used single-time-step model predictive control (MPC) to enable a robot to slowly reach into dense clutter using a quasistatic mechanical model. Rapid reaching in clutter would be desirable, but entails additional challenges due to dynamic phenomena that can lead to higher forces from impacts and other types of contact. In this paper, we present a multi-time-step MPC formulation that enables a robot to rapidly reach a target position in dense clutter, while regulating whole-body contact forces to be below a given threshold. Our controller models the dynamics of the arm in contact with the environment in order to predict how contact forces will change and how the robot’s end effector will move. It also models how joint velocities will influence potential impact forces. At each time step, our controller uses linear models to generate a convex optimization problem that it can solve efficiently. Through tens of thousands of trials in simulation, we show that with our dynamic MPC a simulated robot can, on average, reach goals 1.4 to 2 times faster than our previous controller, while attaining comparable success rates and fewer occurrences of high forces. We also conducted trials using a real 7 degree-of-freedom (DoF) humanoid robot arm with whole-arm tactile sensing. Our controller enabled the robot to rapidly reach target positions in dense artificial foliage while keeping contact forces low
