Sökning: "rörelseplanering"
Visar resultat 1 - 5 av 25 uppsatser innehållade ordet rörelseplanering.
1. Data-Driven Reachability Analysis of Pedestrians Using Behavior Modes : Reducing the Conservativeness in Data-Driven Pedestrian Predictions by Incorporating Their Behavior
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Predicting the future state occupancies of pedestrians in urban scenarios is a challenging task, especially considering that conventional methods need an explicit model of the system, hence introducing data-driven reachability analysis. Data-driven reachability analysis uses data, inherently produced by an unknown system, to perform future state predictions using sets, generally represented by zonotopes. LÄS MER
2. Traction Adaptive Motion Planning for Autonomous Racing
Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)Sammanfattning : Autonomous driving technology is continuously evolving at an accelerated pace. The road environment is always uncertain, which requires an evasive manoeuvre that an autonomous vehicle can take. LÄS MER
3. Data-Driven Motion Planning : With Application for Heavy Duty Vehicles
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Motion planning consists of finding a feasible path of an object between an initial state and a goal state, and commonly constitutes a sub-system of a larger autonomous system. Motion planners that utilize sampling-based algorithms create an implicit representation of the search space via sampling said search space. LÄS MER
4. Real-time motion planning of 6 DOF Collaborative Robot
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Motion planning is an essential component of an autonomous system. This project aims to design a motion planning module to automate the screwing process of radio units. LÄS MER
5. An input-sample method for zonotopic obstacle avoidance with discrete-time control barrier functions
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In this thesis, we consider the motion planning problem for an autonomous vehicle in an obstacle-cluttered environment approximated by zonotopes, and we propose an input sampling algorithm leveraging discrete-time control barrier function conditions (DCBF). Specifically, an optimization-based control barrier function that takes into account the geometric shapes of the vehicle and obstacles is constructed and verified. LÄS MER