Embedded.fm · 29 Aug 2019 · 1h 06m · Episode 301
Carter Frost, president of the Cabrillo College Robotics Club, explains how his team won the 2019 NASA Swarmathon by solving critical localization issues that defeated other universities. The team overcame hardware flaws in the Swarmy robot, specifically IMU magnetometer interference from motors and GPS antennas, by developing a custom soft/hard iron calibration routine. They also implemented a correlated random walk algorithm and drove slower to avoid obstacles, allowing them to collect significantly more resources than competitors despite using the same limited hardware.
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Alex Wischnewski, team lead for the Technical University of Munich (TUM) Autonomous Motorsports team, discusses winning the 2021 Indy Autonomous Challenge. He details the logistical challenges of operating a remote team across time zones during the pandemic, the technical difficulties of driving identical chassis at 136 mph, and the critical role of sensor synchronization and GPS reliability in autonomous racing.
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.
Merihan Alhafnawi, a PhD researcher at the University of Bristol, and Dr. John Oyekan, a Lecturer at the University of Sheffield, discuss swarm robotics, focusing on how groups of robots collaborate to achieve common goals. Alhafnawi explains the concept of 'expressive' swarms that provide visual feedback through touchscreens for social applications like brainstorming, while Oyekan details algorithms inspired by nature for tasks such as mapping invisible hazardous substances in search and rescue operations. The episode covers the technical challenges of collision avoidance, human-swarm interaction, and the cognitive load of controlling large numbers of autonomous agents.
Hackaday editors Mike Szczys and Elliot Williams discuss several hardware hacks, including Joe Barnard’s silo-launched thrust-vectoring model rocket, which required solving pneumatic timing and sensor failures, and Graham Jessup’s 3D-printed robotic face with machine vision tracking. They also cover Daniel Riley’s solar-powered rover, which overcame steering and traction issues through iterative frame modifications, and a robotic ball bouncer using a parallel manipulator and OpenCV. The episode concludes with an analysis of smart speaker false activations and a discussion of Northrop Grumman’s Mission Extension Vehicle, a space tow truck designed to extend satellite life in geosynchronous orbit.
Claire Asher interviews Duncan Russell of Smart City Consultancy about the Smart City Robotics Competition in Milton Keynes, which challenges teams with real-world tasks like coffee service, door opening, and pick-and-pack. Competitors from teams including Mosaic Robotics, Zingers, and MK College discuss specific hardware such as the Tiago, Pepper, and Temi robots, and technical hurdles involving computer vision, sensor integration, and human-robot interaction. The episode highlights the gap between lab precision and unstructured environments, featuring discussions on vision-language-action models, remote monitoring of autonomous shuttles, and the collaborative nature of the event.
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