Robotic Systems Lab

Open Opportunities

Learn to Reach: Collision Aware End-Effector Path Planning & Tracking using Reinforcement Learning ETH Zurich Robotic Systems Lab Other organizations: ETH Competence Center - ETH AI Center Develop a method for collision aware reaching tasks using reinforcement learning and shape encodings of the environment Intelligent Robotics ETH Zurich (ETHZ), Master Thesis

Differentiable Simulation for Precise End-Effector Tracking ETH Zurich Robotic Systems Lab Unlock the potential of differentiable simulation on ALMA, a quadrupedal robot equipped with a robotic arm. Differentiable simulation enables precise gradient-based optimization, promising greater tracking accuracy and efficiency compared to standard reinforcement learning approaches. This project dives into advanced simulation and control techniques, paving the way for improvements in robotic trajectory tracking. Intelligent Robotics Bachelor Thesis, Master Thesis, Semester Project

Reinforcement Learning for Excavation Planning In Terra ETH Zurich Robotic Systems Lab We aim to develop a reinforcement learning-based global excavation planner that can plan for the long term and execute a wide range of excavation geometries. The system will be deployed on our legged excavator. Intelligent Robotics Master Thesis, Semester Project

Model Based Reinforcement Learning ETH Zurich Robotic Systems Lab We want to train an excavator agent to learn in a variety of soil using a fast, GPU-accelerated soil particle simulator in Isaac Sim. Intelligent Robotics, Robotics and Mechatronics Master Thesis, Semester Project

Reinforcement Learning for Particle-Based Excavation in Isaac Sim ETH Zurich Robotic Systems Lab We want to train RL agents on our new particle simulator, accelerated on the GPU via warp in Isaac sim. Intelligent Robotics Master Thesis, Semester Project

Perceptive Reinforcement Learning for Exavation ETH Zurich Robotic Systems Lab In this project, our goal is to leverage precomputed embeddings(VAE in Isaacsim) from 3D earthworks scene reconstructions to train reinforcement learning agents. These embeddings, derived from incomplete point cloud data and reconstructed using an encoder-decoder neural network, will serve as latent representations. The main emphasis is on utilizing these representations to develop and train reinforcement learning policies for digging tasks. Intelligent Robotics Master Thesis, Semester Project

Reiforcement Learning of Pretrained Trasformer Models ETH Zurich Robotic Systems Lab We want to train RL agents on our new particle simulator, accelerated on the GPU via warp in Isaac sim. Information, Computing and Communication Sciences Master Thesis, Semester Project

Multiagent Reinforcement Learning in Terra ETH Zurich Robotic Systems Lab We want to train multiple agents in the Terra environment, a fully end-to-end GPU-accelerated environment for RL training. Information, Computing and Communication Sciences Master Thesis, Semester Project

Propose Your Own Robotics Challenge ETH Zurich Robotic Systems Lab This project invites you to step into the role of an innovator, encouraging you to identify challenges you are passionate about within the field of robotics. Rather than working on predefined problems, you will have the freedom to propose your own project ideas, address real-world issues, or explore cutting-edge topics. This project allows you to define your own research journey. Intelligent Robotics Bachelor Thesis, Master Thesis, Semester Project

Data Driven Simulation for End-to-End Navigation ETH Zurich Robotic Systems Lab Investigate how neural rendering can become the backbone of comprehensive, next generation data-driven simulation Engineering and Technology, Information, Computing and Communication Sciences Internship, Master Thesis