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Erick Lansard

Publications and source records attributed to Erick Lansard.

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Reachability-Based Safe-Start Regions for Approach to a Tumbling Target with Rotating LOS Constraints

This paper presents a reachability-aware guidance architecture for autonomous approach to a tumbling, uncooperative target under a rotating line-of-sight (LOS) docking corridor. The LOS admissible set rotates with the target body frame, producing time-varying polyhedral constraints on the chaser's relative motion, and the design problem is to establish the initial states from which the chaser can safely approach and synchronize with the rotating hold point. A closed-form answer is derived from bounded-thrust relative orbital dynamics, in the form of two analytical safe-start criteria: a directional per-constraint erosion margin, quantifying the corridor margin consumed by rotation-induced drift before the thruster can arrest it, and a synchronization radius, bounding the range over which the apparent rotational velocity can still be cancelled. Closed-loop guidance combines a three-regime tracking law, spanning far-field approach, close body-frame tracking, and synchronized hold, with a receding-horizon quadratic program carrying the rotating corridor constraints and exact discrete relative-motion prediction. The criteria are benchmarked against four standard reachability engines, namely backward and forward polytopic reachable sets, Hamilton--Jacobi level sets, and closed-loop Monte Carlo simulation. The closed-form test is orders of magnitude cheaper than grid-based Hamilton--Jacobi reachability while tracking closed-loop feasibility closely across a parametric sweep. The residual optimism and the gap against Hamilton--Jacobi are structural rather than a method error: requiring the chaser to reach the hold point and co-rotate with it is strictly stronger than requiring it to arrive with arbitrary velocity, and the gap widens with tumble rate. The criteria therefore serve as an onboard go/no-go bound where Hamilton--Jacobi reachability is prohibitively expensive.

eess.SY

Energy-Efficient Data Offloading for Earth Observation Satellite Networks

In Earth Observation Satellite Networks (EOSNs) with a large number of battery-carrying satellites, proper power allocation and task scheduling are crucial to improving the data offloading efficiency. As such, we jointly optimize power allocation and task scheduling to achieve energy-efficient data offloading in EOSNs, aiming to balance the objectives of reducing the total energy consumption and increasing the sum weights of tasks. First, we derive the optimal power allocation solution to the joint optimization problem when the task scheduling policy is given. Second, leveraging the conflict graph model, we transform the original joint optimization problem into a maximum weight independent set problem when the power allocation strategy is given. Finally, we utilize the genetic framework to combine the above special solutions as a two-layer solution for the joint optimization problem. Simulation results demonstrate that our proposed solution can properly balance the sum weights of tasks and the total energy consumption, achieving superior system performance over the current best alternatives.

math.OC