On the Accuracy of Inertial Parameter Estimation of a Free-Flying Robot While Grasping an Object

Ekal, Monica; Ventura, Rodrigo

doi:10.1007/s10846-019-01040-y

Cited by 12 publications

(4 citation statements)

References 16 publications

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“…disturbances. As in [31], m and J = diag([J x , J y , J z ]) are distributed according to m∼N (7.2, (3.2) 2 ), J x , J y , J z ∼N (0.07, (0.015) 2 ). (37)…”

Section: Results: 6 Dof Free-flyer Spacecraftmentioning

confidence: 99%

Chance-Constrained Sequential Convex Programming for Robust Trajectory Optimization

Lew

Bonalli

Pavone

2020

2020 European Control Conference (ECC)

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Planning safe trajectories for nonlinear dynamical systems subject to model uncertainty and disturbances is challenging. In this work, we present a novel approach to tackle chance-constrained trajectory planning problems with nonconvex constraints, whereby obstacle avoidance chance constraints are reformulated using the signed distance function. We propose a novel sequential convex programming algorithm and prove that under a discrete time problem formulation, it is guaranteed to converge to a solution satisfying first-order optimality conditions. We demonstrate the approach on an uncertain 6 degrees of freedom spacecraft system and show that the solutions satisfy a given set of chance constraints.Pr(g(x) ≤ 0) = E(I(x)), with I(x) =    1 if g(x)≤0 0 otherwise.

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“…disturbances. As in [31], m and J = diag([J x , J y , J z ]) are distributed according to m∼N (7.2, (3.2) 2 ), J x , J y , J z ∼N (0.07, (0.015) 2 ). (37)…”

Section: Results: 6 Dof Free-flyer Spacecraftmentioning

confidence: 99%

Chance-Constrained Sequential Convex Programming for Robust Trajectory Optimization

Lew

Bonalli

Pavone

2020

2020 European Control Conference (ECC)

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“…We consider the problem of cargo transport, in which the robot is attached to a payload that results in changes to the inertial properties of the system, resulting in nonlinear dynamics. This system mimics a cargo unloading scenario that is one plausible near-term application of autonomous robots on-board the International Space Station [46,47].…”

Section: Experimental Details and Further Resultsmentioning

confidence: 99%

Safe Active Dynamics Learning and Control: A Sequential Exploration-Exploitation Framework

Lew¹,

Sharma²,

Harrison³

et al. 2020

Preprint

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Safe deployment of autonomous robots in diverse environments requires agents that are capable of safe and efficient adaptation to new scenarios. Indeed, achieving both data efficiency and well-calibrated safety has been a central problem in robotic learning and adaptive control due in part to the tension between these objectives. In this work, we develop a framework for probabilistically safe operation with uncertain dynamics. This framework relies on Bayesian meta-learning for efficient inference of system dynamics with calibrated uncertainty. We leverage the model structure to construct confidence bounds which hold throughout the learning process, and factor this uncertainty into a modelbased planning framework. By decomposing the problem of control under uncertainty into discrete exploration and exploitation phases, our framework extends to problems with high initial uncertainty while maintaining probabilistic safety and persistent feasibility guarantees during every phase of operation. We validate our approach on the problem of a nonlinear free flying space robot manipulating a payload in cluttered environments, and show it can safely learn and reach a goal.

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“…Determining them is more straightforward than in terrestrial robotics, as the targets are typically free-floating and rotating, contrary to objects on earth that are in rest. This can be done before grasping [Christidi-Loumpasefski et al (2017)] to have an initial estimate about the stability, or post-grasping [Ekal and Ventura (2020)] to regulate the estimation and compensate by applying additional force if needed.…”

Section: Dependence On Physical Parametersmentioning

confidence: 99%

On-Orbit Robotic Grasping of a Spent Rocket Stage: Grasp Stability Analysis and Experimental Results

2021

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The increased complexity of the tasks that on-orbit robots have to undertake has led to an increased need for manipulation dexterity. Space robots can become more dexterous by adopting grasping and manipulation methodologies and algorithms from terrestrial robots. In this paper, we present a novel methodology for evaluating the stability of a robotic grasp that captures a piece of space debris, a spent rocket stage. We calculate the Intrinsic Stiffness Matrix of a 2-fingered grasp on the surface of an Apogee Kick Motor nozzle and create a stability metric that is a function of the local contact curvature, material properties, applied force, and target mass. We evaluate the efficacy of the stability metric in a simulation and two real robot experiments. The subject of all experiments is a chasing robot that needs to capture a target AKM and pull it back towards the chaser body. In the V-REP simulator, we evaluate four grasping points on three AKM models, over three pulling profiles, using three physics engines. We also use a real robotic testbed with the capability of emulating an approaching robot and a weightless AKM target to evaluate our method over 11 grasps and three pulling profiles. Finally, we perform a sensitivity analysis to demonstrate how a variation on the grasping parameters affects grasp stability. The results of all experiments suggest that the grasp can be stable under slow pulling profiles, with successful pulling for all targets. The presented work offers an alternative way of capturing orbital targets and a novel example of how terrestrial robotic grasping methodologies could be extended to orbital activities.

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On the Accuracy of Inertial Parameter Estimation of a Free-Flying Robot While Grasping an Object

Cited by 12 publications

References 16 publications

Chance-Constrained Sequential Convex Programming for Robust Trajectory Optimization

Chance-Constrained Sequential Convex Programming for Robust Trajectory Optimization

Safe Active Dynamics Learning and Control: A Sequential Exploration-Exploitation Framework

On-Orbit Robotic Grasping of a Spent Rocket Stage: Grasp Stability Analysis and Experimental Results

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