Dual-arm long-reach manipulators: noncontact motion control strategies

2002 ◽  
Author(s):  
A. Gouo ◽  
D.N. Nenchev ◽  
K. Yoshida ◽  
M. Uchiyama
Keyword(s):  
Motion Control ◽  
Control Strategies ◽  
Dual Arm

HIL Testbed and Motion Control Strategy for the Hybrid Hydraulic-Electric Architecture (HHEA)

2021 ◽  
Author(s):  
Arpan Chatterjee ◽  
Perry Y. Li
Keyword(s):  
Motion Control ◽  
Control Strategy ◽  
Control Strategies ◽  
Electric Machines ◽  
Hardware In The Loop ◽  
System Efficiency ◽  
Electric Motors ◽  
Test Bed ◽  
Road Vehicles ◽  
Precise Control

Abstract The Hybrid Hydraulic-Electric Architecture (HHEA) was proposed in recent years to increase system efficiency of high power mobile machines and to reap the benefits of electrification without the need for large electric machines. It uses a set of common pressure rails to provide the majority of power hydraulically and small electric motors to modulate that power for precise control. This paper presents the development of a Hardware-in-the-loop (HIL) test-bed for testing motion control strategies for the HHEA. Precise motion control is important for off-road vehicles whose utility requires the machine being dexterous and performing tasks exactly as commanded. Motion control for the HHEA is challenging due to its intrinsic use of discrete pressure rail switches to minimize system efficiency or to keep the system within the torque capabilities of the electric motor. The motion control strategy utilizes two different controllers: a nominal passivity based back-stepping controller used in between pressure rail switches and a transition controller used to handle the event of a pressure rail switch. In this paper, the performance of the nominal control under various nominal and rail switching scenarios is experimentally evaluated on the HIL testbed.

scholarly journals Impact motion control of a flexible dual-arm space robot for capturing a spinning object

2019 ◽  
Vol 16 (3) ◽  
pp. 172988141985753
Author(s):  
Xiali Li ◽  
Licheng Wu
Keyword(s):  
Motion Control ◽  
Control Method ◽  
Initial Conditions ◽  
Autonomous Vehicle ◽  
Stable State ◽  
Momentum Conservation ◽  
Space Robot ◽  
Dynamics Response ◽  
The Impact ◽  
Dual Arm

As an autonomous vehicle that moves on the space orbit, a space robot needs to be carefully treated on the motion planning and control method. In this article, the optimal impact and postimpact motion control of a flexible dual-arm space robot capturing a spinning object are considered. Firstly, the dynamic model of the robot systems is built by using Lagrangian formulation. The flexible links are modeled as Euler–Bernoulli beams of two bending modes. Through simulating the system’s postimpact dynamics response, the initial conditions are obtained from the impact model. Next, the initial velocities of base and joint are adjusted to minimize the velocity of the base after the capture according to generalized momentum conservation. After the capture, a proportional–derivative controller is designed to keep the robot system’s stabilization. The simulation results show that joint angles of base and manipulators reach stable state quickly, and motions of the space robots also induce vibrating motions of the flexible manipulators.

scholarly journals Vision-Based Multirotor Following Using Synthetic Learning Techniques

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4794
Author(s):  
Alejandro Rodriguez-Ramos ◽  
Adrian Alvarez-Fernandez ◽  
Hriday Bavle ◽  
Pascual Campoy ◽  
Jonathan P. How
Keyword(s):  
Reinforcement Learning ◽  
Object Detection ◽  
Learning Strategies ◽  
Motion Control ◽  
Domain Adaptation ◽  
Control Strategies ◽  
Synthetic Data ◽  
Real Data ◽  
Stable Convergence ◽  
Learning Techniques

Deep- and reinforcement-learning techniques have increasingly required large sets of real data to achieve stable convergence and generalization, in the context of image-recognition, object-detection or motion-control strategies. On this subject, the research community lacks robust approaches to overcome unavailable real-world extensive data by means of realistic synthetic-information and domain-adaptation techniques. In this work, synthetic-learning strategies have been used for the vision-based autonomous following of a noncooperative multirotor. The complete maneuver was learned with synthetic images and high-dimensional low-level continuous robot states, with deep- and reinforcement-learning techniques for object detection and motion control, respectively. A novel motion-control strategy for object following is introduced where the camera gimbal movement is coupled with the multirotor motion during the multirotor following. Results confirm that our present framework can be used to deploy a vision-based task in real flight using synthetic data. It was extensively validated in both simulated and real-flight scenarios, providing proper results (following a multirotor up to 1.3 m/s in simulation and 0.3 m/s in real flights).

Coordinated motion control of a dual-arm space robot for assembling modular parts

2020 ◽  
Vol 177 ◽  
pp. 627-638
Author(s):  
Shuji Yang ◽  
Hao Wen ◽  
Yunhao Hu ◽  
Dongping Jin
Keyword(s):  
Motion Control ◽  
Space Robot ◽  
Coordinated Motion ◽  
Dual Arm

Coordinated Motion Control of Dual-arm Mobile Manipulator

2003 ◽  
Vol 2003.9 (0) ◽  
pp. 479-480
Author(s):  
Takeshi Araya ◽  
Shinichi Imazawa ◽  
Kouji Kamimizu ◽  
Yoshio Yamamoto
Keyword(s):  
Motion Control ◽  
Mobile Manipulator ◽  
Coordinated Motion ◽  
Dual Arm
Sign in / Sign up

Export Citation Format

Share Document