Podcast Episodes
Back to SearchREMAC: Turning Robot Failures into Better Team Plans
REMAC: Self-reflective and self-evolving multi-agent collaboration for long-horizon robot manipulation In this episode of Embodied AI 101, we explore…
1 month ago
Restore the Sensor Contract: Training-Free Robustness for Brittle VLA Policies
Vision–Language–Action (VLA) policies remain brittle under modest distribution shift. On LIBERO-Plus, contemporary models that solve clean tasks at h…
1 month ago
Before the Robot Touches Anything: Physics-Grounded Deliberation with Embodied Tree of Thoughts
Embodied Tree of Thoughts: Deliberate Manipulation Planning With Embodied World Model In this episode of Embodied AI 101, we explore "Before the Robo…
1 month ago
MemoAct: Why Robot Memory Needs Both a Scratchpad and an Archive
MemoAct: Atkinson–Shiffrin-Inspired Hierarchical Memory-Augmented Policy for Robotic Manipulation In this episode of Embodied AI 101, we explore "Mem…
1 month ago
When Touch Means Something: OmniVTLA and the Missing Contact Layer in Robot Foundation Models
OmniVTLA: Vision-Tactile-Language-Action Models With Semantic-Aligned Tactile Sensing In this episode of Embodied AI 101, we explore "When Touch Mean…
1 month ago
Gaussians as State, Futures as Supervision: Inside GSP-3D
Introduction Learning robust visuomotor policies for bimanual manipulation remains challenging due to the stringent requirements for precise coordina…
1 month ago
SIRModel and the Missing Geometry Layer in Vision–Language Manipulation
Long-horizon robotic manipulation requires a policy to bridge task-level semantic reasoning with metric three-dimensional interaction geometry. Exist…
1 month ago
The Robot That Knows When to Think Twice: Inside τ0-VLA
Long-horizon robot manipulation requires a robot to both execute individual skills reliably and sequence them coherently over extended tasks. Most hi…
1 month ago
When Should a Robot Stop Imagining? RISE and Adaptive World-Action Planning
Introduces dynamic Roll/Stop decision-making in world action models that adapts imagination based on planning benefit, risk, and compute cost for mor…
1 month ago
The Crib as a Causal Laboratory: How a Playing iCub Learns "I Did That"
Learning sensorimotor contingencies—that is, the link between one's actions and their sensory effects—is fundamental to developing body knowledge, un…
1 month ago