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Master Thesis Long Term Human Action Prediction using Advanced AI Models

vor 2 Monaten


Renningen, Baden-Württemberg, Deutschland Bosch Vollzeit
Job Description

Background

Predicting human actions in complex environments is crucial for effective robot operations, particularly in human-populated settings. Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) have shown great potential in addressing these challenges. Despite progress, most studies focus on single human scenarios, with limited research on group actions and human-human interactions.

Research Objective

This master thesis aims to develop a novel approach to integrate humans and their semantic relationships into environmental representations, enabling the recognition and prediction of long-term actions of multiple humans using visual data and AI models.

Key Responsibilities

  • Develop a cutting-edge recognition and prediction model for long-term human actions based on AI models to be used by downstream planning components, and accelerate the testing and deployment of advanced robots and other autonomous systems.
  • Make recognizing and predicting long-term human actions more interpretable by extending the model to provide explanations for its decisions, shedding light on the reasoning behind certain actions.
  • Evaluate the model with open-source datasets, benchmark against state-of-the-art approaches, apply it to downstream tasks (e.g., robot Task and Motion Planning), and demonstrate on real-world applications.

Requirements

  • Education: Master studies in the field of Computer Science, Electrical Engineering, Physics, or comparable with very good grades.
  • Experience and Knowledge: Strong knowledge in Machine Learning, computer vision, and/or robotics, practical experience with Python, PyTorch, TensorFlow, etc.
  • Personality and Working Practice: Eager to learn, open-minded, ready to dive into a topic at the forefront of AI research, robotics, and autonomous driving applications.
  • Languages: Fluent in English, German is a plus.

Additional Information

This thesis requires enrollment at a university. Please attach your CV, transcript of records, examination regulations, and if indicated, a valid work and residence permit.

Diversity and Inclusion

Bosch values diversity and inclusion and welcomes all applications, regardless of gender, age, disability, religion, ethnic origin, or sexual identity.