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April 2026
April 2026
April 30: AERObotics: The Art of Catching Objects in the Air
April 30: AERObotics: The Art of Catching Objects in the Air
Speaker: Prof. Debasish Ghose (Indian Institute of Science, Bangalore )
Speaker: Prof. Debasish Ghose (Indian Institute of Science, Bangalore )
Abstract: A branch of robotics, called mobile robotics, looks at problems related to guiding robots to move over a terrain. Robots in the air are aerial robots and often have similar requirements of guiding themselves from one point to another in the air. A particularly interesting problem is when the robot has to intercept a moving object flying in the air. For instance, how can a robot gripper mounted on a drone catch a ball in the air? In this talk we will see how ideas from the literature on intercepting targets work in the domain of aerial robots.
Abstract: A branch of robotics, called mobile robotics, looks at problems related to guiding robots to move over a terrain. Robots in the air are aerial robots and often have similar requirements of guiding themselves from one point to another in the air. A particularly interesting problem is when the robot has to intercept a moving object flying in the air. For instance, how can a robot gripper mounted on a drone catch a ball in the air? In this talk we will see how ideas from the literature on intercepting targets work in the domain of aerial robots.
Speaker Bio: Prof. Debasish Ghose is an honorary professor at the Indian Institute of Science, Bengaluru. Earlier he was a professor at the same institute in both the Department of Aerospace Engineering and the Robert Bosch Centre for Cyber-physical Systems. He works in the area of guidance and control of autonomous systems, robotics, and game theory. He has held various visiting positions such as at the University of California at Los Angeles, the University of Leicester, and the University of Exeter in the UK. He is a fellow of INAE, NASI, INSA, AAAI, and an associate fellow of AIAA.
Youtube Recording: @Robotics Café
May 2026
May 2026
May 7: Leveraging Predictive Uncertainty for Reliable Model-Based Planning and Control
May 7: Leveraging Predictive Uncertainty for Reliable Model-Based Planning and Control
Speaker: Prof. Arun Kumar Singh (University of Tartu, Estonia)
Speaker: Prof. Arun Kumar Singh (University of Tartu, Estonia)
Abstract: Model-based planning and control remains a dominant paradigm for autonomous decision-making in robotics. However, the underlying models—whether representing robot dynamics or complex environmental interactions—are inherently prone to error. In this talk, I will emphasize the critical need to quantify the uncertainty associated with these learned models and demonstrate how such estimates can be everaged to achieve robust planning and control. I will highlight recent advancements, including my group's latest work on learning uncertainty in a task-aware manner. To ground these theoretical insights, I will showcase practical applications in monocular image-based navigation and autonomous driving.
Abstract: Model-based planning and control remains a dominant paradigm for autonomous decision-making in robotics. However, the underlying models—whether representing robot dynamics or complex environmental interactions—are inherently prone to error. In this talk, I will emphasize the critical need to quantify the uncertainty associated with these learned models and demonstrate how such estimates can be everaged to achieve robust planning and control. I will highlight recent advancements, including my group's latest work on learning uncertainty in a task-aware manner. To ground these theoretical insights, I will showcase practical applications in monocular image-based navigation and autonomous driving.
Speaker Bio: Prof. Arun Kumar Singh is a Professor of Motion Planning at Institute of Technology, University of Tartu, Estonia. He is the PI of the AKS Lab. His researchc interests lie in developing algorithmic foundations of robotics, especially motion planning, control and learning4control. His group consistently publishes in top robotics conferences and journals. He is currently leading a 8M Eruopean project XSCAVE which aims to develop AI based planners and controllers for safety-critical operations involving heavy machineries in Forestry, Logistics and Construction.
Youtube Recording: @ Robotics Café
May 14: Passive dynamics is a good basis for robot design and control. Not.
May 14: Passive dynamics is a good basis for robot design and control. Not.
Speaker: Prof. Andy Ruina (Cornell University, USA)
Speaker: Prof. Andy Ruina (Cornell University, USA)
Abstract: Many airplanes can, or nearly can, glide stably without control. So, it seems natural that the first successful powered flight followed from mastery of gliding. Many bicycles can, or nearly can, when in motion, balance themselves. Bicycle design seems to have evolved to have this feature. Also, we can make toys and ‘robots’ that, like a stable glider or coasting bicycle, stably walk without motors or control in a remarkably human-like way. Again, it thus seems to make sense to use `passive-dynamics’ (uncontrolled dynamics) as a core for developing the control of walking robots and to gain understanding of the control of walking people.
Abstract: Many airplanes can, or nearly can, glide stably without control. So, it seems natural that the first successful powered flight followed from mastery of gliding. Many bicycles can, or nearly can, when in motion, balance themselves. Bicycle design seems to have evolved to have this feature. Also, we can make toys and ‘robots’ that, like a stable glider or coasting bicycle, stably walk without motors or control in a remarkably human-like way. Again, it thus seems to make sense to use `passive-dynamics’ (uncontrolled dynamics) as a core for developing the control of walking robots and to gain understanding of the control of walking people.
That's what I used to think. But, so far, this passive approach has not led to robust walking robots. And, when looked at more carefully, the airplane and bicycle motivations are not as suggestive as they seemed. What about human evolution? Unlike what would be indicated by the passive-dynamic paradigm, human beings did not evolve dynamic bodies and then learn to control them. Rather, people had elaborate control systems way back when we were fish and even when we were worms with no skeletons.
That's what I used to think. But, so far, this passive approach has not led to robust walking robots. And, when looked at more carefully, the airplane and bicycle motivations are not as suggestive as they seemed. What about human evolution? Unlike what would be indicated by the passive-dynamic paradigm, human beings did not evolve dynamic bodies and then learn to control them. Rather, people had elaborate control systems way back when we were fish and even when we were worms with no skeletons.
Now, instead of thinking of good powered walking as passive walking with a small amount of control added, I think of good powered walking, human or robotic, as highly controlled, while optimized mostly for avoiding falls and, secondarily, for minimal actuator use. However, if control is paramount, why is it that uncontrolled passive-dynamic walkers walk so much like humans? It seems that energy optimal, yet robust, control, which is perhaps a proxy for the evolutionary development of human coordination, arrives at solutions that have some features in common with passive-dynamics. Such optimized control, when well done, has most of the motor effort titrated out, yet always at the ready. Thus, highly controlled systems can deceptively-look almost “passive”.
Now, instead of thinking of good powered walking as passive walking with a small amount of control added, I think of good powered walking, human or robotic, as highly controlled, while optimized mostly for avoiding falls and, secondarily, for minimal actuator use. However, if control is paramount, why is it that uncontrolled passive-dynamic walkers walk so much like humans? It seems that energy optimal, yet robust, control, which is perhaps a proxy for the evolutionary development of human coordination, arrives at solutions that have some features in common with passive-dynamics. Such optimized control, when well done, has most of the motor effort titrated out, yet always at the ready. Thus, highly controlled systems can deceptively-look almost “passive”.
The challenge in robotics control today is the posing and solving of appropriate optimization problems. One needs an appropriate control architecture and an appropriate objective (“loss function”). The optimization problem needs to be solvable, or approximately solvable, and the model-based solution policy needs to be robust against unknown disturbances and unknown modeling errors.
The challenge in robotics control today is the posing and solving of appropriate optimization problems. One needs an appropriate control architecture and an appropriate objective (“loss function”). The optimization problem needs to be solvable, or approximately solvable, and the model-based solution policy needs to be robust against unknown disturbances and unknown modeling errors.
Speaker Bio: Prof. Andy Ruina's graduate education was in solid mechanics (in particular, friction) at Brown University. Those interests morphed into biomechanics, dynamics and robotics. Recently, he is primarily interested in the mechanics and control of underactuated motion and locomotion. His lab has made some of the most energy-effective walking robots. See ruina.org for more information.
Youtube Recording: Unfortunately, the recording for this session could not be preserved due to a technical issue.
May 21: UAV Development Cycle: Technical Benchmarks and Lessons in Innovation
May 21: UAV Development Cycle: Technical Benchmarks and Lessons in Innovation
Speaker: Dr. Tanvi Prakash (L&T Precision Engineering and Systems, India)
Speaker: Dr. Tanvi Prakash (L&T Precision Engineering and Systems, India)
Abstract: This session aims to provide participants with an understanding of the latest practices in design and development of high-performance UAVs, drawing on perspectives and challenges from ongoing programmes in the Indian industry. The session will walk participants through the stages of the UAV development cycle, starting from conceptual design and initial sizing, to detailed design and prototyping, and flight-test engineering. The talk aims to give an insight into the technical and logistical rigour involved, with a real- world focus, including some interesting case studies from L&T's UAV portfolio. The talk will show proven ways in which designs can be taken from paper to actual field conditions, by surmounting unique challenges such as terrain, weather, and operational aspects to develop a product that satisfactorily meets customer expectations. The session is targeted at professionals and students, interested in Aircraft Design, New Product Development, Prototyping, and Flight Test Engineering.
Abstract: This session aims to provide participants with an understanding of the latest practices in design and development of high-performance UAVs, drawing on perspectives and challenges from ongoing programmes in the Indian industry. The session will walk participants through the stages of the UAV development cycle, starting from conceptual design and initial sizing, to detailed design and prototyping, and flight-test engineering. The talk aims to give an insight into the technical and logistical rigour involved, with a real- world focus, including some interesting case studies from L&T's UAV portfolio. The talk will show proven ways in which designs can be taken from paper to actual field conditions, by surmounting unique challenges such as terrain, weather, and operational aspects to develop a product that satisfactorily meets customer expectations. The session is targeted at professionals and students, interested in Aircraft Design, New Product Development, Prototyping, and Flight Test Engineering.
Speaker Bio: Dr. Tanvi Prakash is an Aircraft Designer serving as Deputy General Manager (UAV) at Larsen and Toubro, a leading Indian defence contractor. She is an alumnus of VJTI Mechanical (2011) and IIT Bombay Aerospace. She has received the prestigious INAE Young Associate award and the Women in Aviation - Harvard scholarship for Emerging Leaders in Aviation. Her areas of expertise are Aircraft Design, New Product Development, and Flight Test Engineering. Her most recent UAV development assignment was leading the design and development of Teer, a jet-powered aerial target UAV, for the Indian Army. Dr. Tanvi led L&T’s team across the entire development cycle, including Design, Prototyping, Flight Testing, and Serial Production. She also serves as a UAV test pilot, conducting trials across India for various defence customers across India. Currently, she focuses on advancing innovative UAV configurations like tiltrotors, flying bullets, and morphing wings.
Youtube Recording: @ Robotics Café
May 28 (Talk-1): Not Just Where to Move, But How to Coordinate: The Challenge of Dual-Arm Manipulation
May 28 (Talk-1): Not Just Where to Move, But How to Coordinate: The Challenge of Dual-Arm Manipulation
Speaker: Debojit Das (M. Tech. Student, Indian Institute of Technology Gandhinagar)
Speaker: Debojit Das (M. Tech. Student, Indian Institute of Technology Gandhinagar)
Abstract: A robot with two arms does not automatically become twice as capable; sometimes, it becomes twice as confused. Many failures in manipulation do not happen because the robot lacks a trajectory or goal, but because it does not know how the relationship between its arms should evolve during the task, especially in the face of perturbations, or asymmetry in conditions. Through examples such as handovers, pouring, insertion, and cooperative transport, this talk looks at the hidden coordination problem behind dual-arm manipulation, and discusses how structured coordination primitives may offer a path toward more general and reliable robot behavior. The talk addresses two central questions, how a robot can use language and visual context to decide what kind of coordination is needed in the first place, and how it can execute such coordinated control reliably.
Abstract: A robot with two arms does not automatically become twice as capable; sometimes, it becomes twice as confused. Many failures in manipulation do not happen because the robot lacks a trajectory or goal, but because it does not know how the relationship between its arms should evolve during the task, especially in the face of perturbations, or asymmetry in conditions. Through examples such as handovers, pouring, insertion, and cooperative transport, this talk looks at the hidden coordination problem behind dual-arm manipulation, and discusses how structured coordination primitives may offer a path toward more general and reliable robot behavior. The talk addresses two central questions, how a robot can use language and visual context to decide what kind of coordination is needed in the first place, and how it can execute such coordinated control reliably.
Speaker Bio: Debojit Das is an early-career robotics researcher working at the intersection of bimanual manipulation, robotic grasping, control, and coordination. He is currently pursuing a B.Tech-M.Tech Dual Degree in Mechanical Engineering at the Indian Institute of Technology Gandhinagar, where he is a member of the IITGN Robotics Lab and is advised by Prof. Harish P. M. He is presently a visiting researcher at the Smart Robots Design Lab, Tohoku University, Japan, where his work focuses on developing robotic systems capable of more intelligent and coordinated real-world bimanual manipulation.
He has previously worked with the Advanced Robotics Team at Addverb Technologies, contributing to robotics research and development from an industrial perspective. Beyond research, he has also been a TEDx speaker and has spoken at ROSCon India 2025, where he shared his work and ideas with broader technical and public audiences.
More information about his work can be found at Website and Github.
Youtube Recording: TBA
May 28 (Talk-2): Geometry-Grounded Segment Matching for Robust Robot Perception
May 28 (Talk-2): Geometry-Grounded Segment Matching for Robust Robot Perception
Speaker: Rohit Jayanti (Doctoral Student, IIIT-Hyderabad)
Speaker: Rohit Jayanti (Doctoral Student, IIIT-Hyderabad)
Abstract: Modern vision models allow robots to perceive the physical world through semantically meaningful image segments rather than fragile pixel-level keypoints. However, associating these segments across wide-baseline viewpoints, where perspective shifts and up to 180-degree rotations occur, remains a major challenge for standard 2D appearance-based encoders. This talk will discuss SegMASt3R (presented as a Spotlight at NeurIPS 2025), a framework that leverages the spatial inductive biases of 3D foundation models to achieve robust wide-baseline segment matching. This approach outperforms state-of-the-art baselines, including SAM2 and DINOv2, by up to 30% in matching accuracy in challenging settings. Furthermore, the talk will discuss how accurate segment matching translates directly to significant performance gains in key downstream robotics tasks, namely 3D Instance Mapping and Object-Relative Topological Navigation.
Abstract: Modern vision models allow robots to perceive the physical world through semantically meaningful image segments rather than fragile pixel-level keypoints. However, associating these segments across wide-baseline viewpoints, where perspective shifts and up to 180-degree rotations occur, remains a major challenge for standard 2D appearance-based encoders. This talk will discuss SegMASt3R (presented as a Spotlight at NeurIPS 2025), a framework that leverages the spatial inductive biases of 3D foundation models to achieve robust wide-baseline segment matching. This approach outperforms state-of-the-art baselines, including SAM2 and DINOv2, by up to 30% in matching accuracy in challenging settings. Furthermore, the talk will discuss how accurate segment matching translates directly to significant performance gains in key downstream robotics tasks, namely 3D Instance Mapping and Object-Relative Topological Navigation.
Speaker Bio: Rohit is a Graduate Researcher at the Robotics Research Center (RRC), IIIT-Hyderabad, advised by Prof. Madhav Krishna, where his work focuses on 3D scene understanding, geometric foundation models, and topological robot navigation. Previously, he was a founding engineer at Spatial Guide, an augmented-reality (AR) startup accelerated through the Techstars Workforce Development program (in Denver, Colorado, Cohort of 2022).
Youtube Recording: TBA
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