Project Database

This project is intended as a summer project only.

In this project, the student will work closely with other team members to develop data collection pipelines for experiments with an amphibious robot, and use these pipelines to collect and analyze experimental data. Specifically, the student will:

• Use a 4-camera system to track the 3D kinematics of the robot, ideally in real time. This includes calibrating camera intrinsics and extrinsics, labeling data and training a DeepLabCut network or applying marker-tracking libraries for offline tracking, and implementing real-time tracking nodes in ROS 2.
• Synchronize data collected from multiple sources, including cameras, force sensors, motors, and other onboard sensors.
• Visualize the collected data in MuJoCo viewer, RViz, Blender, or other 3D visualization tools.
• Assist with experimental data collection.

The student is expected to be familiar with programming in C/C++ and Python, ROS 2, and robot kinematics. Experience with Docker, Linux kernel development, communication protocols, and computer vision algorithms would be a plus.

Students interested in this project should send the following materials to the project assistant: (1) a resume, (2) a transcript showing relevant courses and grades, and (3) any additional materials that demonstrate their skills and project experience, such as videos, slides, code repositories, or previous project reports.

In nature, animals have many compliant structures that benefit their locomotion. For example, compliant foot/leg structures help adapt to uneven terrain or negotiate obstacles, flexible tails allow efficient undulatory swimming, and muscle-tendon structures help absorb shock and reduce energy loss. Similar compliant structures may benefit salamander-inspired robots as well.

In this study, the student will try simulating compliant structures (the feet of the robot) in Mujoco and optimizing the design. To bridge the sim-to-real gap, the student will first work with other lab members to perform experiments to measure the mechanical properties of a few simple compliant structures. Then, the student needs to simulate these experiments using the flexcomp plugin of Mujoco or theoretical solid mechanics models, and tune the simulation models to match the dynamical response in simulation with the experiments. Afterward, the student needs to optimize the design parameters of the compliant structures in simulation to improve the locomotion performance of the robot while maintaining a small sim-to-real gap. Finally, prototypes of the optimal design will be tested on the physical robot to verify the results.

The student is thus required to be familiar with Python programming, physics engines (preferably Mujoco), and optimization/learning algorithms. The student should also have basic mechanical design abilities to design mechanical structures and perform experiments. Students who have taken the Computational Motor Control course or have experience with data-driven design and solid mechanics would also be preferred.

The student who is interested in this project shall send the following materials to the assistants: (1) resume, (2) transcript showing relevant courses and grades, and (3) other materials that can demonstrate your skills and project experience (such as videos, slides, Git repositories, etc.).

We offer an exciting opportunity for a highly motivated graduate student in Mechanical Engineering to undertake a thesis project focusing on designing and constructing a robotic apparatus to test and validate the impact force of a dinosaur tail strike. This project spans approximately 6 months and requires a combination of mechanical design expertise, force plate measurements, innovation in biomimetic structures, and proficiency in data analysis.

Project Description

The thesis project revolves around designing, building, and controlling a life-sized robotic tail capable of replicating the striking force of a dinosaur’s club-shaped tail. The aim is to accurately measure impact force and velocity using a bone-like material reproduction sourced from fossils we have at the Palaeontological Institute and Museum of the University of Zurich. This endeavor will involve close collaboration with a multidisciplinary team and conducting experiments at our facilities at Empa Dübendorf by Zurich.

Responsibilities

• Utilize mechanical design skills (3D modeling) and motion control (microcontroller designing and programming) to create a functional life-sized Glyptodont's tail.
• Conduct tests to measure impact force and velocity, meticulously documenting experimental procedures and results.
• Employ data analysis techniques, including statistical tools or software, to interpret experimental findings.
• Demonstrate creativity in problem-solving, proposing enhancements to the biomimetic tail design where necessary.
• Collaborate effectively within a team, communicating ideas and contributing to the project's success.

Requirements

Background in mechanical designing with proficiency in 3D modeling.

Expertise in motion control, including microcontroller designing and programming.

Ability to collect, analyze, and interpret experimental data using statistical tools or software.

Strong problem-solving skills with a demonstrated ability to innovate in design and testing.

Excellent communication skills to collaborate within a team and articulate ideas effectively.

Expected Outcomes

Successful creation of a fully functional life-sized Glyptodont's tail within the thesis duration.

Execution of tests to accurately measure impact force and velocity.

Comprehensive documentation of experiments and results.

Recommendations for potential enhancements or modifications based on findings.

If you are a Master's student passionate about pushing the boundaries of robotics, biomimicry, and mechanical engineering and are looking for an engaging thesis project, we encourage you to apply. Please submit your resume/CV along with a cover letter detailing your relevant experience and why you are excited about this exceptional thesis opportunity to Auke Ijspeert as well as Ardian Jusufi.

This project has been taken for 2026 Fall semester.

Background

To improve the indoor autonomy of people with mobility impairments, including wheelchair users, everyday furniture can be augmented with mobility and manipulation capabilities. Such robotic furniture could autonomously reorganize room layouts, clear pathways, transport objects, and grasp and deliver everyday items to users.

This master’s thesis aims to integrate mobile robotic furniture, an origami-inspired robotic arm, markerless perception, and language-based interfaces into a complete assistive mobile manipulation system.

Current Progress

1. Mobile robotic furniture: We have developed a group of mobile robotic furniture units that can autonomously navigate and reconfigure indoor environments.
   References: Publication 1, Publication 2


2. Multi-robot dense coordination: Our Velocity Potential Field Modulation (VPFM) algorithm guides multiple robotic furniture units toward their target poses while avoiding collisions and deadlocks.
   Reference: VPFM publication


3. Markerless tracking and body-language interaction: A multi-view RGB-D system tracks users and furniture units in real time. It provides visual feedback for multi-robot coordination and enables users to control robotic furniture through simple hand motions. The single-view version has been published, while the multi-view version is currently under review.
   References: Single-view system, AI for Good Global Summit 2026 demonstration


4. LLM/VLM supported language interfaces: A natural-language interface supported by a large language model and a vision-language model allows the user to request tasks such as “Bring me a cup of water.” The system can interpret the request, localize the desired object, and identify the furniture on which it is placed. The related paper is under preparation, and a demonstration can be presented during the interview.


5. Origami-inspired robotic arm: The project uses an origami-inspired arm developed by the EPFL Reconfigurable Robotics Lab. The arm can remain folded when not in use and extend for grasping tasks, making it suitable for integration with robotic furniture.
   Reference: Origami-inspired third arm

Thesis Objectives

1. Mechanical and electronic integration: Integrate the origami-inspired arm with a mobile robotic furniture platform. An initial configuration is available, but the student will be encouraged to improve the design to increase the workspace, reachability, and stability of the mobile manipulator.


2. Whole-body control: Develop a controller that coordinates the mobile base and robotic arm. The controller will use feedback from the markerless tracking system and the VLM-based object-grounding module to generate commands for positioning, navigation, grasping, and collision avoidance.


3. End-to-end demonstration: Implement the following scenario:
   • A wheelchair user says, “Bring me a cup of water.”
   • The system interprets the request and localizes the target cup on a static piece of furniture.
   • The system may ask the user for confirmation when the request is ambiguous.
   • A mobile table equipped with the origami arm navigates to the object and positions itself for manipulation.
   • The arm grasps the cup, and the mobile table brings it back to the user.

The final demonstration will integrate speech interaction, visual grounding, markerless tracking, mobile navigation, whole-body control, and robotic grasping.

Desired Candidate Profile

• Experience with ROS 2, C++, and Python;
• Experience with mechanical design or rapid prototyping;
• Interest in mobile manipulation, assistive robotics, robot perception, or human–robot interaction;
• Experience developing real-world robotic applications is an advantage.

This master thesis will be co-supervised by BioRob and RRL

• Contact in BioRob: Lixuan Tang (lixuan.tang@epfl.ch)
• Contact in RRL: Alexander Schuessler (alexander.schuessler@epfl.ch)

This project has been taken for 2026 fall semester

Background

To improve the indoor autonomy of people with mobility impairments, including wheelchair users, everyday furniture can be equipped with mobility and manipulation capabilities. Such robotic furniture could autonomously reorganize room layouts, clear pathways, transport objects, and grasp and deliver everyday items to users.

Coordinating multiple robotic furniture units in confined indoor environments is challenging because their physical shapes and dimensions cannot be neglected. Unlike point robots, furniture units must account for their full geometry when navigating through narrow spaces and interacting with one another.

Current Progress

Our previously developed algorithm, Velocity Potential Field Modulation (VPFM), has demonstrated strong performance in the dense coordination of polytopic robot swarms in 2D environments. Given the current pose and velocity of each robot, together with its target pose, VPFM generates collision-aware motion commands that guide all robots toward their assigned targets while reducing the risk of collisions and deadlocks.

More information is available in our IEEE Robotics and Automation Letters publication and the corresponding open-source repository:

Paper: IEEE RA-L publication

Project Objectives

1. Adapting VPFM to an indoor maze map with static obstacles.
   An ordinary home environment consists of multiple rooms separated by walls and doors, as well as static furniture pieces. To ensure that each mobile robotic furniture unit can arrive at any reachable position in the home environment, combining VPFM with a global path planner can help the swarm of mobile robotic furniture to overcome bottleneck regions and resolve the deadlock.


2. Conduct simulation-based validation.
   Implement and evaluate the proposed methods in simulation using representative dense indoor scenarios. The evaluation should investigate collision avoidance, deadlock resolution, convergence to target poses, computational efficiency, and the benefits of combining a global path planner with the local VPFM coordinator.

This project has been taken for 2026 fall semester

Background

To improve the indoor autonomy of people with mobility impairments, including wheelchair users, everyday furniture can be equipped with mobility and manipulation capabilities. Such robotic furniture could autonomously reorganize room layouts, clear pathways, transport objects, and grasp and deliver everyday items to users.

Coordinating multiple robotic furniture units in confined indoor environments is challenging because their physical shapes and dimensions cannot be neglected. Unlike point robots, furniture units must account for their full geometry when navigating through narrow spaces and interacting with one another.

Current Progress

Our previously developed algorithm, Velocity Potential Field Modulation (VPFM), has demonstrated strong performance in the dense coordination of polytopic robot swarms in 2D environments. Given the current pose and velocity of each robot, together with its target pose, VPFM generates collision-aware motion commands that guide all robots toward their assigned targets while reducing the risk of collisions and deadlocks.

More information is available in our IEEE Robotics and Automation Letters publication and the corresponding open-source repository:

Paper: IEEE RA-L publication

Project Objectives

1. Extend VPFM to height-aware, multi-layer coordination.
   Develop a representation and coordination framework that accounts for the three-dimensional geometry of robotic furniture while maintaining predominantly planar motion. This extension should allow compatible parts of different furniture units to overlap vertically. For example, a low table may move underneath a higher table, and the seat of a chair may pass below a tabletop, while the chair back must still be treated as a potential collision.


2. Conduct simulation-based validation.
   Implement and evaluate the proposed methods in simulation using representative dense indoor scenarios. The evaluation should investigate collision avoidance, deadlock resolution, convergence to target poses, computational efficiency, and the benefits of height-aware coordination compared with the original two-dimensional formulation.