2026 Toronto Robotics Conference

About This Event

The 2026 Toronto Robotics Conference is a two-day University of Toronto Robotics Institute event at University of Toronto Mississauga. The official conference page lists the dates as July 21 to 22, 2026 and describes the event as a multi-track showcase of the latest AI-robotics research across the University of Toronto and the Greater Toronto Area. Luma registration lists University of Toronto Mississauga as the venue and directs attendees to register by July 14, 2026.

• Format: In-person, two-day AI-robotics research conference and showcase.
• Best for: Robotics researchers, AI engineers, graduate students, founders, product leaders, industrial partners, investors, mobility teams, healthcare robotics teams, and organizations evaluating robotics partnerships.
• Core themes: AI-robotics research, autonomous driving, surgical robotics, mobile manipulation, soft robotics, computer vision, robotaxis, startup translation, demos, talent, and industry-academic collaboration.
• CPAI relevance: Robotics is the practical edge of Physical AI, where perception, control, hardware, software, safety, human interaction, and operational deployment must all work together.

Why this topic matters

Physical AI depends on the integration of intelligent software with real machines in real environments. Robotics is where many AI assumptions meet friction: sensing is noisy, motion has consequences, hardware wears down, people must trust the system, and safety cannot be treated as an afterthought. Events like the Toronto Robotics Conference are useful because they show the research, prototypes, people, and partnerships behind future deployable systems.

The official conference page highlights research areas that matter for practical deployment, including autonomous driving, surgical robots, mobile manipulation, soft robotics, and computer vision. These domains are not only academic topics. They are part of the future of transportation, healthcare, manufacturing, logistics, infrastructure inspection, assistive technology, and service robotics.

• Robotics makes AI operational: A robot must perceive, decide, act, and recover in environments that are less predictable than datasets.
• Research translation needs partners: Labs, startups, investors, industry users, and public institutions all shape whether robotics ideas become usable systems.
• Safety and governance are practical: Autonomous vehicles, surgical robots, assistive robots, and mobile systems require clear attention to risk, accountability, validation, and human oversight.
• Talent networks matter: Robotics deployment depends on people who understand mechanical systems, controls, perception, machine learning, human factors, and field operations.
• Canada has a strong robotics opportunity: The GTA’s AI and robotics ecosystem can support companies and institutions working on advanced mobility, healthcare, manufacturing, and embodied systems.

What participants can expect

The official page and registration listing describe a two-day, multi-track event with keynote talks, mini-talks, panel discussion, demos, networking, and a pitch competition. Attendees can expect research talks from AI-robotics experts across the University of Toronto and the GTA, national and international keynote speakers, indoor and outdoor demos from labs and student teams, and networking with faculty, students, alumni, industry partners, and sponsors.

The announced keynote speaker is Tania Morimoto, Associate Professor in Mechanical and Aerospace Engineering and Surgery at UC San Diego, whose research focuses on soft and flexible robots, dexterity, uncertain environments, and human-in-the-loop interfaces. The official page also lists industry mini-talks from Matt Fisch of AEye and Yasaman Soudagar of Exhilarare, and a robotaxis panel moderated by Steven Waslander.

• Keynote and mini-talk programming on leading AI-robotics research and industry applications.
• A panel on robotaxis and the implications of autonomous vehicles for Toronto and broader society.
• Indoor and outdoor demonstrations from university labs and student teams.
• The Two Small Fish Pitch Competition for University of Toronto students and postdoctoral researchers with concept-stage AI-robotics ideas.
• Networking with faculty, trainees, alumni, sponsors, startups, industry partners, and robotics ecosystem leaders.

Who should attend

This conference is a strong fit for people who want to understand where AI-robotics research is heading and how that research may become useful in products, public systems, industrial tools, and new ventures. It is also useful for organizations looking to recruit talent, form partnerships, sponsor research, or identify emerging technology directions.

• Robotics and AI researchers: Useful for seeing related work across the GTA ecosystem and identifying collaboration opportunities.
• Graduate students and postdoctoral researchers: Useful for networking, presenting ideas, learning from senior researchers, and exploring startup pathways.
• Industrial partners and technology companies: Useful for identifying talent, research partnerships, demos, and emerging robotics capabilities.
• Founders and investors: Useful for understanding concept-stage robotics opportunities and the realities of technical commercialization.
• Policy, mobility, and safety stakeholders: Useful for engaging with the robotaxis panel and broader questions about autonomous systems in cities.
• CPAI members and practitioners: Useful for connecting Physical AI concepts to working prototypes, research labs, real hardware, and deployment questions.

How this connects to CPAI’s mission

CPAI focuses on practical AI adoption, Physical AI, robotics, governance, and operational deployment. The Toronto Robotics Conference is a direct fit because it sits at the intersection of AI research, embodied systems, hardware, startups, industry collaboration, and human impact. It can help CPAI’s audience see how robotics ideas move from labs into demos, early ventures, and deployment conversations.

The event is also useful because it includes both technical depth and ecosystem-building. Physical AI does not mature through algorithms alone. It requires talent pipelines, funders, mentors, test environments, partners, user feedback, safety thinking, and organizations willing to evaluate real systems. This conference brings many of those ingredients into one setting.

• It connects AI research to physical systems that must work in the world.
• It surfaces deployment questions around autonomy, human-in-the-loop control, dexterity, mobility, and safety.
• It helps businesses and institutions meet the talent and labs shaping future robotics capabilities.
• It supports the kind of ecosystem collaboration that practical AI adoption requires.

Practical questions to prepare

Attendees can get more from the conference by arriving with specific questions about how robotics research becomes deployable. These questions are useful for evaluating demos, talking with researchers, and connecting the event to business, public-sector, or implementation goals.

• Which robotics capabilities are mature enough to evaluate now, and which are still primarily research-stage?
• What sensing, control, safety, and human-interface assumptions are required for each system to work?
• Where could robotics improve industrial, healthcare, mobility, inspection, or service workflows?
• What evidence would be needed before a robot or autonomous system could be piloted in a real operation?
• What partnerships would help move a lab concept toward a product, field trial, or responsible deployment?
• How should governance, liability, public trust, and human oversight shape the adoption of autonomous systems?

Practical takeaways

• Understand the research frontier: Use keynotes, mini-talks, and demos to see where AI-robotics research is advancing across mobility, healthcare, manipulation, soft robotics, and perception.
• Evaluate physical deployment readiness: Ask how each system handles sensing limits, uncertain environments, safety constraints, and human interaction.
• Connect with the ecosystem: Meet researchers, students, founders, sponsors, and industry partners who may support future projects or partnerships.
• Learn from startup translation: Use the pitch competition to understand how early robotics ideas are framed for impact, mentorship, and commercialization.
• Think about governance early: Apply questions from autonomous vehicles and surgical robotics to broader Physical AI deployment.
• Identify talent and collaboration pathways: Look for labs, students, teams, or partners whose work aligns with your organization’s operational challenges.
• Turn inspiration into next steps: After the event, identify which ideas are worth tracking, piloting, sponsoring, or exploring through a focused conversation.