{"668475":{"#nid":"668475","#data":{"type":"event","title":"Ph.D. Dissertation Defense - Ashwin Lele","body":[{"value":"\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003ETitle\u003C\/span\u003E\u003C\/strong\u003E\u003Cem\u003E\u003Cspan\u003E:\u0026nbsp; \u003C\/span\u003E\u003C\/em\u003E\u003C\/span\u003E\u003C\/span\u003E\u003Cem\u003ESpiking Neural Networks Enabled Circuits and Systems for Edge Robots\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003ECommittee:\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EDr. \u003C\/span\u003E\u003Cspan\u003EArijit Raychowdhury, ECE, Chair\u003C\/span\u003E\u003Cspan\u003E, Advisor\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EDr. \u003C\/span\u003E\u003Cspan\u003ESuman Datta, ECE\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EDr. \u003C\/span\u003E\u003Cspan\u003EJustin Romberg, ECE\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EDr. \u003C\/span\u003E\u003Cspan\u003EVisvesh Sathe, ECE\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EDr. \u003C\/span\u003E\u003Cspan\u003EAlexey Tumanov, CoC\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ERobotic computing at the edge needs to meet multiple constraints on power and form factor while delivering the required performance for power-hungry neural network kernels. This work proposed spiking neural network (SNN) alternatives and augmentations for algorithms and circuits for edge robots. We show SNN-driven locomotion for power-constrained hexapod robots, SNN-augmented target tracking for high-speed aerial robots and SNN-assisted visual navigation for size-critical micro-robots. The first part of the work extends rhythmic leg movement of insects to an SNN-based gait generator to demonstrate an online training method. We then utilize an event-based vision sensor as the sensory front-end to the hexapod locomotion to show the first spike-only closed-loop robotic platform. In the second part, we observe that SNN and event-camera forms a sensor-processor pair well-suited for high-speed processing while frame-camera with convolutional neural network (CNN) suits the applications with the high-accuracy requirement. This trade-off between accuracy vs. latency in the event and frame-based visual processing arises from the detailed temporal and spatial resolutions captured by event and frame cameras respectively. We utilize these complementary strengths to build high-speed target identification and tracking system with SNN providing high-speed but noisy target estimates with CNN preserving the lost accuracy by providing reliable periodic anchors. We build a heterogeneous SoC with low-power RRAM compute-in-memory mapping CNN and high-speed SRAM compute-near-memory accelerating SNN. The final part of the work generalizes the idea of multi-modal processing applied in the previous chapters to divide the robotic computing workloads between trainable-CNN for perception tasks and physics-based symbolic processing for motion encoding tasks. Our SoC uses RRAM compute-near-memory kernels to accelerate CNN-based perception while SRAM compute-in-memory carries out SNN-based localization on micro-robots. To summarize, this work attempted to substitute and augment the compute-constrained robotic hardware with SNN for energy saving and performance improvement.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Spiking Neural Networks Enabled Circuits and Systems for Edge Robots"}],"uid":"28475","created_gmt":"2023-07-13 21:28:28","changed_gmt":"2023-07-14 14:05:16","author":"Daniela Staiculescu","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-07-21T11:00:00-04:00","event_time_end":"2023-07-21T13:00:00-04:00","event_time_end_last":"2023-07-21T13:00:00-04:00","gmt_time_start":"2023-07-21 15:00:00","gmt_time_end":"2023-07-21 17:00:00","gmt_time_end_last":"2023-07-21 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online","extras":[],"related_links":[{"url":"https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_NDE3ODE1ZjgtYjczMi00NDE5LThlYmUtOTE5OTYyZjAxODdh%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%226f30fa3a-5c53-40ff-90eb-2dad1829ac34%22%7d","title":"Microsoft Teams Meeting link"}],"groups":[{"id":"434381","name":"ECE Ph.D. Dissertation Defenses"}],"categories":[],"keywords":[{"id":"192484","name":"PhD Defense, graduate students"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}