Project Database

This project has been taken for the 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 reorganize room layouts, clear pathways, transport objects, and deliver everyday items to users.

This semester project focuses on the user-centric design of such an assistive environment. The goal is to understand the everyday challenges, functional limitations, and interaction needs of wheelchair users, and to investigate how multiple user interfaces can provide accessible and intuitive control of robotic furniture.

Current Progress

1. Mobile robotic furniture: A group of robotic furniture units capable of autonomous navigation and room reconfiguration.
   References: Publication 1, Publication 2


2. Markerless body-language interaction: A multi-view RGB-D system tracks users and furniture in real time and enables simple gesture-based interaction.
   References: AI for Good 2026 demonstration


3. LLM/VLM-supported natural-language interface: Users can give commands such as “Bring me a cup of water,” while the system interprets the request and identifies relevant objects and furniture.


4. Origami-inspired robotic arm: A compact foldable robotic arm can be integrated with robotic furniture or the wheelchair for grasping and delivery tasks.
   Reference: Origami-inspired third arm


5. Tablet interface: A bird's-eye visualization allows users to select predefined layouts or reposition furniture through drag-and-drop interaction.

Project Objectives

1. User-Centric Study: Investigate the everyday challenges faced by wheelchair users through literature review and existing user surveys. Understand how different mobility impairments affect functional abilities and interaction needs, identify meaningful assistive applications, and define requirements for future user studies.


2. Multimodal Interface Integration: Investigate how origami arm, gesture, tablet, natural language, and/or other interfaces can complement each other. The aim is to ensure that users with different abilities or under different conditions always have an accessible way to trigger, modify, or stop an assistive function.


3. Interface Exploration: Depending on the student's interests, further develop or evaluate one specific interaction modality.

Desired Candidate Profile

• Strong interest in user-centric research, assistive technology, rehabilitation, or human–robot interaction;
• Interest in understanding how mobility impairments affect functional abilities and interaction with technology;
• Background in neuroscience, neuroengineering, biomedical engineering, rehabilitation, robotics, HCI, or related fields is welcome;
• Experience with user studies, experimental design, rapid prototyping, or robotic systems is an advantage.

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)