Seeing Robotics and Machine Vision as Dynamical Systems

EE Times Current · 13 Oct 2023 · 48m

What this episode covers

Dr. Yulia Sandamirskaya, now leading the Neuromorphic Computing Group at Zurich University of Applied Sciences (ZHAW), discusses her work applying dynamical systems theory to robotics and machine vision. She details her previous role at Intel, where she utilized the Loihi neuromorphic platform to develop real-time robotic applications, including drone control and human-robot interaction. The episode also features commentary from Ralph Etienne-Cummings of Johns Hopkins University on the challenges of embodiment, active vision, and the need for heterogeneous hardware architectures.

Mentioned

Companies
Intel, Zurich University of Applied Sciences, Johns Hopkins University, Italian Institute of Technology, Delft University of Technology, Queensland University of Technology
Products
event-based camera
Chips
Loihi, Dynap-SE

Other shows on the same ground, closest first.

  • Robot Talk · 34m

    Episode Four - Robot Senses: perceiving the world

    Matt Watson of Opteran Technologies explains how reverse-engineering honeybee brains enables efficient, low-power collision avoidance and SLAM, contrasting this with the high compute demands of supervised deep learning. Dr. Perla Maiolino of the Oxford Robotics Institute discusses CySkin, a flexible, large-area artificial skin using capacitive triangular modules for tactile perception and manipulation. Dr. Dimitrios Kanoulas of UCL addresses the challenge of fusing multi-sensor data (LiDAR, cameras, IMUs) to handle uncertainty and real-time planning in dynamic, unstructured environments.

  • Robot Talk · 22m

    Episode 124: Robots in the performing arts - Amy LaViers

    Amy LaViers, director of the Robotics, Automation, and Dance (RAD) Lab, discusses her interdisciplinary work bridging robotics and performing arts. She explains how her senior thesis on the 'unrideable bicycle' and choreographer Twila Tharp’s concepts of stability led to her current research on creating large datasets of annotated human movement for AI. LaViers also details the operational challenges of live performance robotics, where equipment failure is not an option, and describes her iterative, experimental approach to choreographing with non-humanoid machines like the HAL robot and piezo robots.

  • The Robot Report Podcast · 46m

    NVIDIA GTC24 and R-24 recap

    Mike Weitzman and Gene Demaitre of The Robot Report recap their attendance at NVIDIA GTC24 in San Jose and the R24 robotics conference in Odense, Denmark. They highlight NVIDIA's new Blackwell architecture and Jetson Thor system-on-chip designed for humanoid robots, alongside the industry's shift toward generative AI and foundation models for robotics. The episode also details the unique collaborative ecosystem in Denmark, featuring companies like Universal Robots and Mobile Industrial Robots, and discusses the rapid development of physical humanoid robots such as Agility Digit, Unitree H1, and Boston Dynamics' robots.

  • The Robot Report Podcast · 1h 24m

    Marc Raibert on the future of robotics

    Marc Raibert, founder of Boston Dynamics and director of the AI Institute, discusses his transition from leading Boston Dynamics for 30 years to establishing a new long-term R&D organization backed by Hyundai. He outlines the AI Institute's four pillars—cognitive AI, athletic AI, organic hardware, and ethics—and describes ambitious goals like robots learning tasks by observation and performing complex mobile manipulation. Raibert also addresses the current state of humanoid robotics, the challenges of battery life and dexterity, and his vision for a future where robots assist rather than replace human labor.

  • Robot Talk · 24m

    Episode 155: Making aerial robots smarter - Melissa Greeff

    Melissa Greeff, an Assistant Professor at Queen's University and leader of the Robora Lab, discusses her research on autonomous aerial systems, including vision-based navigation and safe learning-based control. She details projects involving drones landing on surface vessels for maritime operations, tiny drones using custom optimization solvers for agile flight, and multi-robot teams where aerial vehicles teach ground robots routes. Greeff emphasizes the challenges of bridging perception and control, limited onboard compute, and the gap between academic prototypes and persistent industrial autonomy.

The summary, chapters and topics are generated from the episode’s audio by this directory, not written by EE Times Current. The episode itself belongs to its publisher.