IEEE ICVES 2026 Plenary Speakers
IEEE ICVES 2026 will feature distinguished plenary speakers from academia and industry, covering key topics in robotics navigation, space situational awareness, trustworthy AI, and autonomous systems. All plenary sessions are open to all registered participants.
Plenary sessions at a glance:
- Sessions cover both academic research and industry applications.
- Topics include SLAM, multi-target tracking, trustworthy AI, and autonomous machines.
- Plenary attendance is included with the conference registration.
Plenary Session 1 — From Ground to Orbit
Innovations in Robotics Navigation & Space Situational Awareness
A unified view of two seemingly distant problems — robotic navigation on the ground and tracking space debris in orbit — through the lens of random finite set (RFS)-based multi-object state estimation.
| Speaker | Prof. Martin Adams |
| Affiliation | Dept. Electrical Engineering, Advanced Mining Technology Centre (AMTC), Universidad de Chile |
| Session type | Plenary Session |
What this plenary covers
1. Two problems, one framework
Autonomous navigation, multi-target tracking and data registration are estimation problems relevant to a wide range of applications. For robotic navigation, feature-based SLAM is critical. In Space Situational Awareness (SSA), multi-target tracking is of major importance, since the space debris population is so high that chain reaction collisions — known as the Kessler syndrome — are increasingly likely.
2. Why multi-object state estimation is challenging
Three core challenges: unknown numbers (objects appear and disappear over time), noisy sensors (spatial errors, false alarms, missed detections), and data association (determining which measurement belongs to which object).
3. RFS-based solutions
Bayesian Random Finite Sets (RFSs) model the multi-object configuration itself as a single random variable. Using finite set statistics (FISST), these methods estimate target/map feature number and state values, while circumventing fragile measurement-to-state data association.
4. New multi-object solutions for SLAM and SSA
The SLAM state is modelled as a mixed distribution jointly representing the vector-valued trajectory and the RFS-valued map, yielding competitive and often superior results. FISST-based SSA in low Earth orbit is also demonstrated, detecting and tracking multiple space debris via telescopic measurements using Riemannian manifold geometry.
About the speaker
Martin Adams is Professor of Electrical Engineering and former director of the Dept. of Electrical Engineering, University of Chile. He is also a principle investigator in the industrially sponsored Advanced Mining Technology Centre (AMTC). He obtained his first degree in Engineering Science at the University of Oxford, U.K., in 1988 and continued to study for a D.Phil. at the Robotics Research Group, University of Oxford, which he received in 1992. He continued his research in autonomous robot navigation as a project leader and part time lecturer at the Institute of Robotics, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland. He was employed as a Guest Professor and taught control theory in St. Gallen (Switzerland) from 1994 to 1995. From 1996 to 2000, he served as a senior research scientist in robotics and control, in the field of semiconductor assembly automation, at the European Semiconductor Equipment Centre (ESEC), Switzerland. From 2000 to 2010, he was Associate Professor at the School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore. His research work focuses on autonomous robot navigation, sensing, sensor data interpretation and control, and he has published many technical papers in these fields. He has been the principle investigator and leader of many robotics and industrially sponsored projects, coordinating researchers from local industries and local and overseas universities, has served as associate editor on various journal and conference editorial boards and as Chair of the Robotics & Automation Chapter, Chile.
Plenary Session 2 — Debugging the Ghost in the Machine
Developing Trustworthy Machines and Recruiting AI to Help
A look at the challenges of deploying autonomous machines in high-stakes applications, and how engineers are recruiting AI to transform assurance, verification and certification.
| Speaker | Dr. Mauricio Castillo-Effen |
| Affiliation | Lockheed Martin Advanced Technology Laboratories |
| Session type | Plenary Session (Industry) |
What this plenary covers
1. The "ghost in the machine"
Mistakes, bugs and security vulnerabilities are one of the main hurdles to widespread deployment of autonomous machines in high-stakes applications. How do we develop, verify, validate and successfully deploy machines we can trust?
2. New lifecycle models for trustworthy autonomy
Unpacking new lifecycle models that could allow us to update machines long after deployment, and why the industry must transition from linear processes with over-dimensioned assurance to a leaner, more agile form of assurance that compounds knowledge over time.
3. Recruiting AI for the heavy lifting
Using digital twins to test and verify machines and to enable certification by analysis, and — as a promising path — using AI to prove mathematically that software does what it is supposed to do.
About the speaker
Bio Mauricio Castillo-Effen, Ph.D. Mauricio is a Research Fellow in Trustworthy AI and Autonomy at Lockheed Martin's Advanced Technology Laboratories. With over 25 years of R&D experience, Mauricio has advanced autonomy and assurance across multiple industries, including aerospace, energy, oil and gas, and healthcare, by leading programs funded by the US Government and industry. He has been developing solutions for deploying complex decision-making systems in high-criticality applications by focusing on verification, validation, test, evaluation, and certification challenges that enable rapid capability deployment. He has received multiple Technical Excellence and Innovation Awards for transitioning cutting-edge technologies from laboratory to operational environments. He holds over 20 patents in robotics and autonomy, has taught at universities worldwide, and earned Ph.D., M.Sc., and B.Sc. degrees in Electrical Engineering.
Who can attend
Plenary sessions are open to all registered ICVES 2026 participants, including authors, students, young professionals and attendees. Registration for the conference covers plenary attendance; no separate registration fee is required.
Contact
For questions about the plenary programme, please contact the Program Chair through the conference website.
For general inquiries, please contact: registration2026@ieee-icves.org
