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For the next few weeks, TechCrunch\u2019s robotics newsletter Actuator will be running Q&As with some of the top minds in robotics. Subscribe here<\/a> for future updates.<\/p>\n Part 1:<\/strong> CMU\u2019s Matthew Johnson-Roberson<\/a> Ken Goldberg is a professor and the William S. Floyd Jr. Distinguished Chair in Engineering at UC Berkeley, a co-founder and chief scientist at robotics parcel sorting startup Ambidextrous and a fellow at IEEE.\u00a0<\/span><\/p>\n What role(s) will generative AI play in the future of robotics?<\/b><\/p>\n Although the rumblings started a bit earlier, 2023 will be remembered as the year when generative AI transformed Robotics. Large language models like ChatGPT can allow robots and humans to communicate in natural language. Words evolved over time to represent useful concepts from \u201cchair\u201d to \u201cchocolate\u201d to \u201ccharisma.\u201d Roboticists also discovered that large Vision-Language-Action<\/span><\/i> models can be trained to facilitate robot perception and to control the motions of robot arms and legs. Training requires vast amounts of data so labs around the world are now collaborating to share data. Results are pouring in and although there are still open questions about generalization, the impact will be profound.<\/span><\/p>\n Another exciting topic is \u201cMulti-Modal models\u201d in two senses of multi-modal:<\/span><\/p>\n What are your thoughts on the humanoid form factor?<\/b><\/p>\n I\u2019ve always been skeptical about humanoids and legged robots, as they can be overly sensational and inefficient, but I\u2019m reconsidering after seeing the latest humanoids and quadrupeds from Boston Dynamics, Agility and Unitree. Tesla has the engineering skills to develop low-cost motors and gearing systems at scale. Legged robots have many advantages over wheels in homes and factories to traverse steps, debris and rugs. Bimanual (two-armed) robots are essential for many tasks, but I still believe that simple grippers will continue to be more reliable and cost-effective than five-fingered robot hands.<\/span><\/p>\n Following manufacturing and warehouses, what is the next major category for robotics?<\/b><\/p>\n After the recent union wage settlements, I think we\u2019ll see many more robots in manufacturing and warehouses than we have today. Recent progress in self-driving taxis has been impressive, especially in San Francisco where driving conditions are more complex than Phoenix. But I\u2019m not convinced that they can be cost-effective. For robot-assisted surgery, researchers are exploring \u201cAugmented Dexterity\u201d \u2014 where robots can enhance surgical skills by performing low-level subtasks such as suturing.<\/span><\/p>\n How far out are true general-purpose robots?<\/b><\/p>\n I don\u2019t expect to see true AGI and general-purpose robots in the near future. Not a single roboticist I know worries about robots stealing jobs or becoming our overlords.<\/span><\/p>\n Will home robots (beyond vacuums) take off in the next decade?<\/b><\/p>\n I predict that within the next decade we will have affordable home robots that can declutter \u2014 pick up things like clothes, toys and trash from the floor and place them into appropriate bins. Like today\u2019s vacuum cleaners, these robots will occasionally make mistakes, but the benefits for parents and senior citizens will outweigh the risks.<\/span><\/p>\n \u00a0What important robotics story\/trend isn\u2019t getting enough coverage?<\/b><\/p>\n Robot motion planning. This is one of the oldest subjects in robotics \u2014 how to control the motor joints to move the robot tool and avoid obstacles. Many think this problem has been solved, but it hasn\u2019t.\u00a0\u00a0<\/span><\/p>\n Robot \u201csingularities\u201d are a fundamental problem for all robot arms; they are very different from Kurzweil\u2019s hypothetical point in time when AI surpasses humans. Robot singularities are points in space where a robot stops unexpectedly and must be manually reset by a human operator. Singularities arise from the math needed to convert desired straight-line motion of the gripper into the corresponding motions for each of the six robot joint motors. At certain points in space, this conversion becomes unstable (similar to a divide-by-zero error), and the robot needs to be reset.<\/span><\/p>\n For repetitive robot motions, singularities can be avoided by tedious manual fine-tuning of repetitive robot motions to adjust them such that they never encounter singularities. Once such motions are determined, they are repeated over and over again. But for the growing generation of applications where robot motions are not repetitive, including palletizing, bin-picking, order fulfillment and package sorting, singularities are common. They are a well-known and fundamental problem as they disrupt robot operations at unpredictable times (often several times per hour). <\/span>I co-founded a new startup, Jacobi Robotics, that <\/span>implements efficient algorithms that are *guaranteed* to avoid singularities. This can significantly increase reliability and productivity for all robots.\u00a0\u00a0<\/span><\/p>\n<\/p><\/div>\n
Part 2:<\/strong> Toyota Research Institute\u2019s Max Bajracharya and Russ Tedrake<\/a>
Part 3: <\/strong>Meta\u2019s Dhruv Batra<\/a>
Part 4:<\/strong> Boston Dynamics\u2019 Aaron Saunders<\/a><\/p>\n\n
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