AgEmerge Podcast 190 with Tyler Niday | Bonsai Robotics and Practical Autonomous Farm Solutions
Most farms struggle with dust, inefficiency, and labor shortages—but Tyler Niday of Bonsai Robotics reveals how AI-driven machinery is changing the game by transforming existing equipment into autonomous workhorses.
Inspired by biology, Bonsai Robotics is making some of agriculture's toughest environments manageable. Tyler shares how autonomous orchard shakers are improving nut harvest efficiency by up to 40%, while converting shuttle trucks into multi-functional farm platforms can save growers hundreds of thousands of dollars in equipment costs.
Monte and Tyler explore the industry's evolution from retrofitting machines with autonomous capabilities to developing full-platform solutions, including Bonsai's Amiga series. These adaptable systems support precision spraying, harvesting, and crop scouting.
Before co-founding Bonsai Robotics, Tyler began in mechanical engineering and helped develop vision systems at Blue River Technology and gained hands-on learning at Orchard Machinery Corporation.
If you've wondered what the future of practical farm automation really looks like, this episode offers a firsthand look at innovations in the field today.
Main Topics:
- The evolution of AI and robotics in agriculture, from Blue River to Bonsai Robotics
- Managing perception challenges in dusty orchard environments using vision and AI models
- The design and versatility of the Amiga autonomous platform for multiple crop applications
- Practical case studies: autonomous nut harvesting, orchard spraying, and equipment modularity
- Connectivity solutions in remote environments, including Starlink utilization
- Future opportunities: precision variances mapping, crop-specific scouting, and ecosystem integration
Visit Bonsai Robotics: https://bonsairobotics.ai/
Watch additional farm autonomy solutions: https://www.youtube.com/watch?v=g7MDT2NlNAs&t=1s
Timestamps:
00:00 - Introduction and podcast purpose
00:10 - Tyler’s background and journey into ag tech
01:23 - Transition from conventional to regenerative agriculture
02:23 - The role of AI and perception challenges in dust environments
07:48 - Vision-only AI vs LiDAR debate and dust interference
08:41 - Handling environment-specific solutions like lens cleaning in dust
12:04 - Scalability of perception models across crops
12:58 - Training AI models on dusty environments and data fusion
14:22 - Equipment adaptations for dusty environments (air systems, cleaning)
16:16 - Focus on specialty crops as a starting point for autonomy
16:45 - Collaborations with OEMs like Floria and OMC
17:30 - Managing connectivity in remote farm locations
19:07 - Starlink and cellular solutions for remote operations
20:31 - Developing new equipment and platform ecosystem
21:30 - The Amiga platform's different configurations and applications
24:39 - From first principles equipment modification to autonomy
25:44 - Strategic move into precision spraying and harvest-related automation
28:28 - Future autonomous applications for open-field crops
29:42 - Case study: Autonomous orchard shaker and efficiency gains
34:47 - Vision system improvements for equipment safety and speed
37:44 - Autonomous nut shaker and harvesting efficiency
41:46 - Future of crop variability mapping and individual plant management
45:37 - The evolving role of vision-based AI in complex farming tasks
47:13 - Returning value through data management and software ecosystems
49:21 - Industry collaboration, standards, and evolving equipment
52:25 - Closing remarks and future outlook
Note: The episode is packed with insights into the latest in ag robotics. Whether you're a farmer, engineer, or researcher, you'll find takeaways that can inform your practices and strategic planning in an increasingly autonomous future.
