910 research outputs found
Trajectory generation of space telerobots
The purpose is to review a variety of trajectory generation techniques which may be applied to space telerobots and to identify problems which need to be addressed in future telerobot motion control systems. As a starting point for the development of motion generation systems for space telerobots, the operation and limitations of traditional path-oriented trajectory generation approaches are discussed. This discussion leads to a description of more advanced techniques which have been demonstrated in research laboratories, and their potential applicability to space telerobots. Examples of this work include systems that incorporate sensory-interactive motion capability and optimal motion planning. Additional considerations which need to be addressed for motion control of a space telerobot are described, such as redundancy resolution and the description and generation of constrained and multi-armed cooperative motions. A task decomposition module for a hierarchical telerobot control system which will serve as a testbed for trajectory generation approaches which address these issues is also discussed briefly
Modeling & control of a space robot for active debris removal
Space access and satellites lifespan are increasingly threatened by the great amount of debris in Low Earth Orbits (LEO). Among the many solutions proposed in the literature so far, the emphasis is put here on a robotic arm mounted on a satellite to capture massive debris, such as dead satellites or launch vehicle upper stages. The modeling and control of such systems are investigated throughout the paper. Dynamic models rely on an adapted Newton-Euler algorithm, and control algorithms are based on the recent structured H infinity method. The main goal is to efficiently track a target point on the debris while using simple PD-like controllers to reduce computational burden. The structured H infinity framework proves to be a suitable tool to design a reduced-order robust controller that catches up with external disturbances and is simultaneously compatible with current space processors capacities
Simultaneous Capture and Detumble of a Resident Space Object by a Free-Flying Spacecraft-Manipulator System
The article of record as published may be found at https://doi.org/10.3389/frobt.2019.00014A maneuver to capture and detumble an orbiting space object using a chaser spacecraft equipped with a robotic manipulator is presented. In the proposed maneuver, the capture and detumble objectives are integrated into a unified set of terminal constraints. Terminal constraints on the end-effector’s position and velocity ensure a successful capture, and a terminal constraint on the chaser’s momenta ensures a post-capture chaser-target system with zero angular momentum. The manipulator motion required to achieve a smooth, impact-free grasp is gradually stopped after capture, equalizing the momenta across all bodies, rigidly connecting the two vehicles, and completing the detumble of the newly formed chaser-target system without further actuation. To guide this maneuver, an optimization-based approach that enforces the capture and detumble terminal constraints, avoids collisions, and satisfies actuation limits is used. The solution to the guidance problem is obtained by solving a collection of convex programming problems, making the proposed guidance approach suitable for onboard implementation and real-time use. This simultaneous capture and detumble maneuver is evaluated through numerical simulations and hardware-in-the-loop experiments. Videos of the numerically simulated and experimentally demonstrated maneuvers are included as Supplementary Material
Instantaneous Momentum-Based Control of Floating Base Systems
In the last two decades a growing number of robotic applications such as autonomous drones, wheeled robots and industrial manipulators started to be employed in several human environments. However, these machines often possess limited locomotion and/or manipulation capabilities, thus reducing the number of achievable tasks and increasing the complexity of robot-environment interaction. Augmenting robots locomotion and manipulation abilities is a fundamental research topic, with a view to enhance robots participation in complex tasks involving safe interaction and cooperation with humans. To this purpose, humanoid robots, aerial manipulators and the novel design of flying humanoid robots are among the most promising platforms researchers are studying in the attempt to remove the existing technological barriers. These robots are often modeled as floating base systems, and have lost the assumption -- typical of fixed base robots -- of having one link always attached to the ground.
From the robot control side, contact forces regulation revealed to be fundamental for the execution of interaction tasks. Contact forces can be influenced by directly controlling the robot's momentum rate of change, and this fact gives rise to several momentum-based control strategies. Nevertheless, effective design of force and torque controllers still remains a complex challenge. The variability of sensor load during interaction, the inaccuracy of the force/torque sensing technology and the inherent nonlinearities of robot models are only a few complexities impairing efficient robot force control.
This research project focuses on the design of balancing and flight controllers for floating base robots interacting with the surrounding environment. More specifically, the research is built upon the state-of-the-art of momentum-based controllers and applied to three robotic platforms: the humanoid robot iCub, the aerial manipulator OTHex and the jet-powered humanoid robot iRonCub. The project enforces the existing literature with both theoretical and experimental results, aimed at achieving high robot performances and improved stability and robustness, in presence of different physical robot-environment interactions
Optimizing Dynamic Trajectories for Robustness to Disturbances Using Polytopic Projections
This paper focuses on robustness to disturbance forces and uncertain
payloads. We present a novel formulation to optimize the robustness of dynamic
trajectories. A straightforward transcription of this formulation into a
nonlinear programming problem is not tractable for state-of-the-art solvers,
but it is possible to overcome this complication by exploiting the structure
induced by the kinematics of the robot. The non-trivial transcription proposed
allows trajectory optimization frameworks to converge to highly robust dynamic
solutions. We demonstrate the results of our approach using a quadruped robot
equipped with a manipulator.Comment: Final accepted version to the IEEE/RSJ International Conference on
Intelligent Robots and Systems (IROS) 2020. Supplementary video:
https://youtu.be/vDesP7IpTh
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