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1. Towards Robust Planar Translations using Delta-manipulator Arrays

   Thompson, S.; Mannam, P.; Temel, Z.; Kroemer, O. (May 2021, International Conference of Robotics and Automation)

   null (Ed.)

   Distributed manipulators - consisting of a set of actuators or robots working cooperatively to achieve a manipulation task - are robust and flexible tools for performing a range of planar manipulation skills. One novel example is the delta array, a distributed manipulator composed of a grid of delta robots, capable of performing dexterous manipulation tasks using strategies incorporating both dynamic and static contact. Hand-designing effective distributed control policies for such a manipulator can be complex and time consuming, given the high-dimensional action space and unfamiliar system dynamics. In this paper, we examine the principles guiding development and control of such a delta array for a planar translation task. We explore policy learning as a robust cooperative control approach, allowing for smooth manipulation of a range of objects, showing improved accuracy and efficiency over baseline human-designed policies. 

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2. Contact Optimization for Non-Prehensile Loco-Manipulation via Hierarchical Model Predictive Control

   https://doi.org/10.1109/ICRA48891.2023.10160507  

   Rigo, Alberto; Chen, Yiyu; Gupta, Satyandra K; Nguyen, Quan (May 2023, IEEE)

   Recent studies on quadruped robots have focused on either locomotion or mobile manipulation using a robotic arm. However, legged robots can manipulate large objects using non-prehensile manipulation primitives, such as planar pushing, to drive the object to the desired location. This paper presents a novel hierarchical model predictive control (MPC) for contact optimization of the manipulation task. Using two cascading MPCs, we split the loco-manipulation problem into two parts: the first to optimize both contact force and contact location between the robot and the object, and the second to regulate the desired interaction force through the robot locomotion. Our method is successfully validated in both simulation and hardware experiments. While the baseline locomotion MPC fails to follow the desired trajectory of the object, our proposed approach can effectively control both object's position and orientation with minimal tracking error. This capability also allows us to perform obstacle avoidance for both the robot and the object during the loco-manipulation task. 

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3. Encoder-less Robot Control for Space Operations with Continuum Robots

   Frazaelle, C.G.; Walker, I.D.; AlAttar, A.; Kormushev, P. (March 2021, IEEE Aerospace Conference)

   null (Ed.)

   Continuum robots have strong potential for application in Space environments. However, their modeling is challenging in comparison with traditional rigid-link robots. The Kinematic-Model-Free (KMF) robot control method has been shown to be extremely effective in permitting a rigid-link robot to learn approximations of local kinematics and dynamics (“kinodynamics”) at various points in the robot’s task space. These approximations enable the robot to follow various trajectories and even adapt to changes in the robot’s kinematic structure. In this paper, we present the adaptation of the KMF method to a three-section, nine degrees-of-freedom continuum manipulator for both planar and spatial task spaces. Using only an external 3D camera, we show that the KMF method allows the continuum robot to converge to various desired set points in the robot’s task space, avoiding the complexities inherent in solving this problem using traditional inverse kinematics. The success of the method shows that a continuum robot can “learn” enough information from an external camera to reach and track desired points and trajectories, without needing knowledge of exact shape or position of the robot. We similarly apply the method in a simulated example of a continuum robot performing an inspection task on board the ISS. 

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4. Contact-less Manipulation of Millimeter-scale Objects via Ultrasonic Levitation

   https://doi.org/10.1109/BioRob49111.2020.9224384  

   Nakahara, Jared; Yang, Boling; Smith, Joshua R. (November 2020, 2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob))

   null (Ed.)

   Although general purpose robotic manipulators are becoming more capable at manipulating various objects, their ability to manipulate millimeter-scale objects are usually limited. On the other hand, ultrasonic levitation devices have been shown to levitate a large range of small objects, from polystyrene balls to living organisms. By controlling the acoustic force fields, ultrasonic levitation devices can compensate for robot manipulator positioning uncertainty and control the grasping force exerted on the target object. The material agnostic nature of acoustic levitation devices and their ability to dexterously manipulate millimeter-scale objects make them appealing as a grasping mode for general purpose robots. In this work, we present an ultrasonic, contact-less manipulation device that can be attached to or picked up by any general purpose robotic arm, enabling millimeter-scale manipulation with little to no modification to the robot itself. This device is capable of performing the very first phase-controlled picking action on acoustically reflective surfaces. With the manipulator placed around the target object, the manipulator can grasp objects smaller in size than the robot's positioning uncertainty, trap the object to resist air currents during robot movement, and dexterously hold a small and fragile object, like a flower bud. Due to the contact-less nature of the ultrasound-based gripper, a camera positioned to look into the cylinder can inspect the object without occlusion, facilitating accurate visual feature extraction. 

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5. Time Delay Control of a High-DOF Robot Manipulator Through Feedback Linearization Based Predictor

   https://doi.org/https://doi.org/10.1115/DSCC2019-8915  

   Bagheri, Mostafa; Naseradinmousavi, Peiman; Krstic, Miroslav (November 2019, ASME 2019 Dynamic Systems and Control Conference)

   We formulate a predictor-based controller for a high-DOF manipulator to compensate a time-invariant input delay during a pick-and-place task. Robot manipulators are widely used in tele-manipulation systems on the account of their reliable, fast, and precise motions while they are subject to large delays. Using common control algorithms on such delay systems can cause not only poor control performance, but also catastrophic instability in engineering applications. Therefore, delays need to be compensated in designing robust control laws. As a case study, we focus on a 7-DOF Baxter manipulator subject to three different input delays. First, delay-free dynamic equations of the Baxter manipulator are derived using the Lagrangian method. Then, we formulate a predictor-based controller, in the presence of input delay, in order to track desired trajectories. Finally, the effects of input delays in the absence of a robust predictor are investigated, and then the performance of the predictor-based controller is experimentally evaluated to reveal robustness of the algorithm formulated. Simulation and experimental results demonstrate that the predictor-based controller effectively compensates input delays and achieves closed-loop stability. 

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