MSc Robotics, Systems and Control · ETH Zürich

Jan Kamm

Engineering.In the Way of Water focus project at ETH, we built a fleet of 26 autonomous, coordinated boats from scratch. I worked across the stack: hardware, sensor fusion, the first state estimator, and motion planning. Within months the fleet went from first prototype to public performances, including Time Space Existence during the 2025 Venice Architecture Biennale.

Research.Planning motion for that fleet became my research. I do my research with Raffaello D'Andrea and Antonio Terpin at the Institute for Dynamic Systems and Control, ETH Zürich.

Research →Email Scholar ↗GitHub ↗LinkedIn ↗

Current work

01 / 05

Unconstrained encounter01 / 02

An analytical characterization of optimal collision-free motion through contact.

Fleet algorithm01 / 02

Iteratively insert contacts and solve an algebraic system for collision-free motion.

Grid to double helix01 / 02

Lightspeed computation for small teams, scalable to fleets of one million robots.

Doesn’t scale with…

01 / 02

Computation time (ms, log)

dimension

dimension: SCI computation time in milliseconds
Setting	Median	25th percentile	75th percentile	2.5th percentile	97.5th percentile	Solves
2 dimensions	3.081	1.679	5.183	0.268	15.836	50
3 dimensions	3.502	2.187	4.763	0.414	14.215	50
5 dimensions	2.543	1.577	3.916	0.270	16.650	50
10 dimensions	2.816	1.658	5.859	0.281	39.731	50

tolerance

tolerance: SCI computation time in milliseconds
Setting	Median	25th percentile	75th percentile	2.5th percentile	97.5th percentile	Solves
2% tolerance	5.785	3.735	8.766	0.280	26.379	50
0.2% tolerance	5.677	3.714	8.753	0.307	26.599	50
0.02% tolerance	5.974	4.287	9.134	0.291	27.377	50

discretization

discretization: SCI computation time in milliseconds
Setting	Median	25th percentile	75th percentile	2.5th percentile	97.5th percentile	Solves
10 time steps	5.576	3.579	8.348	0.274	23.008	48
15 time steps	5.576	3.579	8.348	0.274	23.008	48
25 time steps	5.576	3.579	8.348	0.274	23.008	48
35 time steps	5.576	3.579	8.348	0.274	23.008	48
50 time steps	5.576	3.579	8.348	0.274	23.008	48
75 time steps	5.576	3.579	8.348	0.274	23.008	48
100 time steps	5.576	3.579	8.348	0.274	23.008	48
150 time steps	5.576	3.579	8.348	0.274	23.008	48
200 time steps	5.576	3.579	8.348	0.274	23.008	48

time horizon

time horizon: SCI computation time in milliseconds
Setting	Median	25th percentile	75th percentile	2.5th percentile	97.5th percentile	Solves
1 s horizon	2.960	1.583	5.048	0.346	8.986	50
3 s horizon	2.874	1.494	4.806	0.346	9.013	50
10 s horizon	2.786	1.473	4.751	0.332	7.673	50
30 s horizon	2.778	1.456	4.865	0.356	7.965	50
100 s horizon	2.910	1.427	4.727	0.333	8.427	50

Grows with contacts

02 / 02

Computation time (ms, log)

contacts: SCI computation time in milliseconds
Setting	Median	25th percentile	75th percentile	2.5th percentile	97.5th percentile	Solves
0 contacts	0.268	0.261	0.284	0.243	0.344	36
1 contact	1.593	1.486	1.689	1.379	2.499	65
2 contacts	2.825	2.609	3.068	2.419	3.977	57
3 contacts	4.652	4.170	5.284	3.519	14.019	49
4 contacts	6.819	5.883	8.359	4.859	26.278	34
5 contacts	9.017	7.397	11.416	6.317	50.072	23
6 contacts	12.162	9.430	14.548	8.238	42.469	18
7 contacts	20.834	17.269	60.463	16.340	1036.667	8
8 contacts	28.142	26.360	32.263	25.358	39.581	4
9 contacts	58.949	53.083	65.553	24.751	126.517	5
10 contacts	146.921	146.921	146.921	146.921	146.921	1

10 robots · 300 instances

Planning complexity grows with contacts, reflecting the encounters between robots.

Obstacles01 / 03

Box bounds, obstacle avoidance, and prioritized planning all with one framework.

A new paradigm for planning robotic fleets: optimize the encounters between robots and reconstruct the motion in between. This structure lets us plan collision-free motion for a million robots.

Education

2026–
ETH Zürich
MSc Robotics, Systems and Control
2022–2026
ETH Zürich
BSc Electrical Engineering and Information Technology
2018–2022
MNG Rämibühl
Bilingual Matura, Physics and Applied Mathematics

Experience

2024–2026
Institute for Dynamic Systems and Control
Robotics engineer & researcher, ETH Zürich, with Raffaello D'Andrea
2024–2026
IYPT Switzerland
Board member, Zürich
2026
Swiss Armed Forces
Reconnaissance soldier, fire-command platoon

Selected awards & recognition

2023
Nobel Week (SIYSS)
Presented research at SIYSS, including an invitation to the Nobel Prize Ceremonies in Stockholm, Sweden.
2023
Swiss Youth in Science
Winning finalist, rated “excellent” for research in analytical fluid dynamics.
2023
Swiss Physical Society Award
One of five students recognized for outstanding achievements in physics in Switzerland.
2022
International Young Physicists’ Tournament (IYPT)
World champion and gold medal, Swiss team captain · Timișoara, Romania.
2022
Swiss Young Physicists’ Tournament (SYPT)
1st place in both the team and individual rankings.
2021
International Young Physicists’ Tournament (IYPT)
Silver medal, Swiss team captain · Kutaisi, Georgia.
2021
Swiss Young Physicists’ Tournament (SYPT)
1st place in both the team and individual rankings.
2021
Náboj Mathematics Competition
1st place in Switzerland, Senior category · Zürich.