State, shape, and parameter estimation of space objects from range images

Abstract

-An architecture for the estimation of dynamic state, geometric shape, and model parameters of objects in orbit using on-orbit cooperative 3-D vision sensors is presented. This has application in many current and projected space missions, such as automated satellite capture and servicing, debris capture and mitigation, and large space structure assembly and maintenance. The method presented here consists of three parts: (1) kinematic data fusion, which condenses sensory data into coarse kinematic surrogate measurements; (2) Kalman filtering, which filters these surrogate measurements and extracts the full dynamic state and model parameters of the target; and (3) shape estimation, which uses filtered pose information and the raw sensory data to build a body-fixed probabilistic map of the target's shape. This method does not rely on feature detection, optical flow, or model matching, but rather exploits the well-modeled dynamics of objects in space using the Kalman filter. The architecture is computationally fast since only coarse measurements need to be provided to the Kalman filter. This paper will illustrate the three steps of the architecture in the context of rigid body (satellite and debris) estimation and flexible structure estimation.

A Review of Robotics Technologies for On-Orbit Services

“…Assuming that an object is not acted upon by any external force and moment, the motion of the target satellite was predicted in [60]. Litcher and Dubowsky, using 3-D vision sensors, proposed an architecture for estimation of dynamic state, geometric shape, and model parameters of an object in orbit, with potential application to a satellite capturing [61]. It is very desirable to predict the motion of a target as soon as possible.…”

Tracking Control of Spacecraft by Dynamic Output Feedback - Passivity-Based Approach

“…ω of the target can be measured in some way, for example, the target www.intechopen.com motion estimation method using image information (Lichter & Dubowsky, 2004;Tanaka et al, 2007 …”

On the Capture of Tumbling Satellite by a Space Robot

“…Some of the problems that need to be considered can be outlined as follows; (i) estimation of the motion profile of the grasping point is necessary. When the inertia characteristics of the target are unknown, obtaining a long term estimation is challenging [30], [29], [31]; (ii) the planning algorithm has to design a feasible approaching trajectory, that minimizes the contact forces during the impact-phase, as well as the reactions transferred to the base during the manipulator approaching motion; (iii) if the approach is interrupted, reliable estimation should be performed again; (iv) during the postimpact phase the momentum initially stored in the target satellite, transfers to the chaser and imposes difficulties from the viewpoint of base attitude control. Furthermore, releasing the target satellite leads to collision risks with the manipulator links and spacecraft's base.…”

“…We assume that; a 1 ) the target undergoes constant linear and angular motion and its angular momentum is known in advance (precise estimation is not necessary) [29], [30]; a 2 ) there are no external forces acting on the entire system (chaser plus target). No gas-jet thrusters are used on the chaser's base.…”