VISTA Lab

Vision, Intelligence, and Systems Technology in Automation

Advancing the frontiers of robotics through cutting-edge research in computer vision, artificial intelligence, and autonomous systems

Explore Our Research

About VISTA Lab

The VISTA (Vision, Intelligence, and Systems Technology in Automation) Lab is a cutting-edge robotics research facility dedicated to advancing the field of autonomous systems. Under the leadership of Prof. Pierre-Yves Lajoie, our team pushes the boundaries of what's possible in robotics, computer vision, and artificial intelligence.

Our research focuses on developing intelligent systems that can perceive, understand, and interact with complex real-world environments. We work on fundamental problems in robotics while maintaining a strong emphasis on practical applications that can benefit society.

The lab fosters an interdisciplinary environment where computer scientists, engineers, and researchers collaborate to solve challenging problems in autonomous navigation, machine learning, and human-robot interaction.

25+
Research Projects
15
Team Members
50+
Publications
8
Active Collaborations

Research Areas

🤖

Autonomous Navigation

Developing advanced algorithms for robot localization, mapping, and path planning in complex, dynamic environments. Our work includes SLAM, visual odometry, and multi-robot coordination systems.

👁️

Computer Vision

Creating robust vision systems for object detection, recognition, and scene understanding. We focus on deep learning approaches, 3D perception, and real-time visual processing for robotic applications.

🧠

Machine Learning for Robotics

Applying cutting-edge ML techniques to robotic systems, including reinforcement learning, imitation learning, and neural network architectures optimized for real-time robotic control.

🤝

Human-Robot Interaction

Investigating natural and intuitive ways for humans and robots to collaborate. Our research covers gesture recognition, social robotics, and adaptive interfaces for human-robot teams.

🌐

Multi-Agent Systems

Exploring coordination and cooperation among multiple robotic agents. We develop distributed algorithms for task allocation, consensus, and swarm robotics applications.

Edge Computing

Optimizing AI algorithms for deployment on resource-constrained robotic platforms. We focus on model compression, efficient inference, and real-time processing on embedded systems.

Our Team

PYL

Prof. Pierre-Yves Lajoie

Principal Investigator & Lab Director

Prof. Lajoie leads the VISTA Lab with expertise in autonomous systems, computer vision, and robotics. His research focuses on developing intelligent algorithms for robot perception and decision-making in complex environments.

AS

Dr. Alex Smith

Senior Research Scientist

Specializes in SLAM algorithms and multi-robot systems. Dr. Smith has published extensively on cooperative localization and distributed mapping techniques.

MJ

Maria Johnson

PhD Student

Working on deep learning approaches for visual perception in robotics. Maria's research focuses on developing robust neural networks for object detection and scene understanding.

DC

David Chen

PhD Student

Research focuses on human-robot interaction and natural language processing for robotic systems. David is developing intuitive interfaces for robot command and control.

SP

Sarah Park

MSc Student

Investigating reinforcement learning algorithms for autonomous navigation. Sarah's work aims to develop adaptive control strategies for mobile robots in dynamic environments.

JW

James Wilson

Research Engineer

Manages lab infrastructure and develops software frameworks for robotic experimentation. James specializes in real-time systems and embedded programming.

Recent Publications

Distributed SLAM in Dynamic Environments using Multi-Agent Cooperation

P.Y. Lajoie, A. Smith, M. Johnson

International Conference on Robotics and Automation (ICRA), 2025

Deep Learning for Robust Visual Odometry in Challenging Conditions

M. Johnson, P.Y. Lajoie, D. Chen

IEEE Transactions on Robotics, 2024

Natural Language Interface for Human-Robot Collaboration

D. Chen, S. Park, P.Y. Lajoie

International Conference on Human-Robot Interaction (HRI), 2024

Efficient Neural Network Deployment on Resource-Constrained Robotic Platforms

J. Wilson, A. Smith, P.Y. Lajoie

IEEE Robotics and Automation Letters (RA-L), 2024

Reinforcement Learning for Adaptive Path Planning in Unknown Environments

S. Park, M. Johnson, P.Y. Lajoie

International Conference on Intelligent Robots and Systems (IROS), 2023