Related papers: Energy-Aware Planning-Scheduling for Autonomous Ae…
Decision problems encountered in practice often possess a highly dynamic and uncertain nature. In particular fast changing forecasts for parameters (e.g., photovoltaic generation forecasts in the context of energy management) pose large…
Collision avoidance in unknown obstacle-cluttered environments may not always be feasible. This paper focuses on an emerging paradigm shift in which potential collisions with the environment can be harnessed instead of being avoided…
Robots are frequently tasked to gather relevant sensor data in unknown terrains. A key challenge for classical path planning algorithms used for autonomous information gathering is adaptively replanning paths online as the terrain is…
Robot task planning is an important problem for autonomous robots in long-horizon challenging tasks. As large pre-trained models have demonstrated superior planning ability, recent research investigates utilizing large models to achieve…
This paper presents a new approach for formulating the delivery problem by drones with general energy consumption models where the drones visit a set of places to deliver parcels to customers. Drones can perform multiple trips that start…
Unmanned Aerial Vehicle (UAV) technology is a promising solution for providing high-quality mobile services to ground users, where a UAV with limited service coverage travels among multiple geographical user locations (e.g., hotspots) for…
In this paper, we address the power-aware scheduling of sporadic constrained-deadline hard real-time tasks using dynamic voltage scaling upon multiprocessor platforms. We propose two distinct algorithms. Our first algorithm is an off-line…
Modern cyber-physical systems (e.g., robotics systems) are typically composed of physical and software components, the characteristics of which are likely to change over time. Assumptions about parts of the system made at design time may…
This paper addresses motion replanning in human-robot collaborative scenarios, emphasizing reactivity and safety-compliant efficiency. While existing human-aware motion planners are effective in structured environments, they often struggle…
Global navigation satellite systems (GNSS) denied environments/conditions require unmanned aerial vehicles (UAVs) to energy-efficiently and reliably fly. To this end, this study presents perception-and-energy-aware motion planning for UAVs…
Aerospace production volumes have increased over time and robotic solutions have been progressively introduced in the aeronautic assembly lines to achieve high-quality standards, high production rates, flexibility and cost reduction.…
This paper presents a mission system and the therein implemented algorithms for path planning in a time-varying environment based on graph methods. The basic task of the introduced path planning algorithms is to find a time-optimal path…
An important goal of modern scheduling systems is to efficiently manage power usage. In energy-efficient scheduling, the operating system controls the speed at which a machine is processing jobs with the dual objective of minimizing energy…
We present planning challenges, methods and preliminary results for a new model-based paradigm for earth observing systems in adaptive remote sensing. Our heuristically guided constraint optimization planner produces coordinated plans for…
Path planning methods for autonomous unmanned aerial vehicles (UAVs) are typically designed for one specific type of mission. This work presents a method for autonomous UAV path planning based on deep reinforcement learning (DRL) that can…
Motion planning in off-road environments requires reasoning about both the geometry and semantics of the scene (e.g., a robot may be able to drive through soft bushes but not a fallen log). In many recent works, the world is classified into…
We examine two configurations for parallel hybrid electric aircraft, one with, and one without, a mechanical connection between the engines and the electric motors. For this two designs, we then review the power allocation problem in the…
Hybrid locomotion, which combines multiple modalities of locomotion within a single robot, enables robots to carry out complex tasks in diverse environments. This paper presents a novel method for planning multi-modal locomotion…
The innovative concept of Electric Aircraft is a challenging topic involving different control objectives. For instance, it becomes possible to reduce the size and the weight of the generator by using the battery as an auxiliary generator…
This paper describes a technique for the autonomous mission planning of robotic swarms in high risk environments where agent disablement is likely. Given a swarm operating in a known area, a central command system generates measurements…