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+methods.+While+recent+research+has+demonstrated+performance+gains+in+scenarios+with+comparatively+smooth+dynamics+and%252C+thus%252C+smooth+optimization+landscapes%252C+research+on+leveraging+differentiable+simulators+for+contact-rich+scenarios%252C+such+as+legged+locomotion%252C+is+scarce.+This+may+be+attributed+to+the+discontinuous+nature+of+contact%252C+which+introduces+several+challenges+to+optimizing+with+analytic+gradients.+The+purpose+of+this+paper+is+to+determine+if+analytic+gradients+can+be+beneficial+even+in+the+face+of+contact.+Our+investigation+focuses+on+the+effects+of+different+soft+and+hard+contact+models+on+the+learning+process%252C+examining+optimization+challenges+through+the+lens+of+contact+simulation.+We+demonstrate+the+viability+of+employing+analytic+gradients+to+learn+physically+plausible+locomotion+skills+with+a+quadrupedal+robot+using+Short-Horizon+Actor-Critic+(SHAC)%252C+a+learning+algorithm+leveraging+analytic+gradients%252C+and+draw+a+comparison+to+a+state-of-the-art+RL+algorithm%252C+Proximal+Policy+Optimization+(PPO)%252C+to+understand+the+benefits+of+analytic+gradients.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.f7bc372deb71ce3dcf058c91c2bd2849%3frik%3dpxcVbnw3NuAC8A%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Quadrupedal+Locomotion&FORM=IRPRST&ck=E4C58A4B43769F4412C924B3004A7276&selectedIndex=15&itb=0)
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