diff --git a/CHANGELOG.md b/CHANGELOG.md
index e1350cb..9ac53c7 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -10,6 +10,12 @@ its affiliates is strictly prohibited.
 -->
 # Changelog
 
+## Latest Commit
+
+### BugFixes & Misc.
+- Fix bug in evaluator to account for dof maximum acceleration and jerk.
+- Add unit test for different acceleration and jerk limits.
+
 ## Version 0.7.2
 
 ### New Features
diff --git a/src/curobo/types/state.py b/src/curobo/types/state.py
index 2655e46..4be430d 100644
--- a/src/curobo/types/state.py
+++ b/src/curobo/types/state.py
@@ -81,7 +81,7 @@ class JointState(State):
     @staticmethod
     def from_numpy(
         joint_names: List[str],
-        position: np.ndarry,
+        position: np.ndarray,
         velocity: Optional[np.ndarray] = None,
         acceleration: Optional[np.ndarray] = None,
         jerk: Optional[np.ndarray] = None,
@@ -91,6 +91,8 @@ class JointState(State):
         vel = acc = je = None
         if velocity is not None:
             vel = tensor_args.to_device(velocity)
+        else:
+            vel = pos * 0.0
         if acceleration is not None:
             acc = tensor_args.to_device(acceleration)
         else:
diff --git a/src/curobo/wrap/reacher/evaluator.py b/src/curobo/wrap/reacher/evaluator.py
index 863b6a9..c48beb9 100644
--- a/src/curobo/wrap/reacher/evaluator.py
+++ b/src/curobo/wrap/reacher/evaluator.py
@@ -218,12 +218,13 @@ def compute_smoothness(
     scale_dt = (1 / dt_score).view(-1, 1, 1)
     abs_acc = torch.abs(acc) * (scale_dt**2)
     # mean_acc_val = torch.max(torch.mean(abs_acc, dim=-1), dim=-1)[0]
-    max_acc_val = torch.max(torch.max(abs_acc, dim=-1)[0], dim=-1)[0]
+    max_acc_val = torch.max(abs_acc, dim=-2)[0]  # batch x dof
     abs_jerk = torch.abs(jerk) * scale_dt**3
     # calculate max mean jerk:
     # mean_jerk_val = torch.max(torch.mean(abs_jerk, dim=-1), dim=-1)[0]
-    max_jerk_val = torch.max(torch.max(abs_jerk, dim=-1)[0], dim=-1)[0]
+    max_jerk_val = torch.max(abs_jerk, dim=-2)[0]  # batch x dof
     acc_label = torch.logical_and(max_acc_val <= max_acc, max_jerk_val <= max_jerk)
+    acc_label = torch.all(acc_label, dim=-1)
     return (acc_label, smooth_cost(abs_acc, abs_jerk, dt_score))
 
 
diff --git a/tests/motion_gen_eval_test.py b/tests/motion_gen_eval_test.py
new file mode 100644
index 0000000..3e64832
--- /dev/null
+++ b/tests/motion_gen_eval_test.py
@@ -0,0 +1,72 @@
+#
+# Copyright (c) 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# NVIDIA CORPORATION, its affiliates and licensors retain all intellectual
+# property and proprietary rights in and to this material, related
+# documentation and any modifications thereto. Any use, reproduction,
+# disclosure or distribution of this material and related documentation
+# without an express license agreement from NVIDIA CORPORATION or
+# its affiliates is strictly prohibited.
+#
+
+# Third Party
+import pytest
+import torch
+
+# CuRobo
+from curobo.types.base import TensorDeviceType
+from curobo.types.robot import JointState
+from curobo.util_file import get_robot_configs_path, join_path, load_yaml
+from curobo.wrap.reacher.evaluator import TrajEvaluatorConfig
+from curobo.wrap.reacher.motion_gen import MotionGen, MotionGenConfig, MotionGenPlanConfig
+
+
+def run_motion_gen(robot_file, evaluate_interpolated_trajectory, max_acc, max_jerk):
+    tensor_args = TensorDeviceType()
+    world_file = "collision_test.yml"
+    robot_data = load_yaml(join_path(get_robot_configs_path(), robot_file))
+    dof = len(robot_data["robot_cfg"]["kinematics"]["cspace"]["joint_names"])
+
+    robot_data["robot_cfg"]["kinematics"]["cspace"]["max_acceleration"] = [
+        max_acc for i in range(9)
+    ]
+    robot_data["robot_cfg"]["kinematics"]["cspace"]["max_jerk"] = [max_jerk for i in range(9)]
+
+    motion_gen_config = MotionGenConfig.load_from_robot_config(
+        robot_data,
+        world_file,
+        tensor_args,
+        use_cuda_graph=False,
+        maximum_trajectory_dt=1.5,
+        evaluate_interpolated_trajectory=evaluate_interpolated_trajectory,
+    )
+    motion_gen = MotionGen(motion_gen_config)
+
+    retract_cfg = motion_gen.get_retract_config()
+
+    start_state = JointState.from_position(retract_cfg.view(1, -1).clone())
+    goal_state = JointState.from_position(retract_cfg.view(1, -1).clone() + 0.2)
+
+    result = motion_gen.plan_single_js(
+        start_state, goal_state, MotionGenPlanConfig(max_attempts=5, enable_graph_attempt=10)
+    )
+    return result
+
+
+@pytest.mark.parametrize(
+    "robot_file, evaluate_interpolated_traj, max_acc, max_jerk",
+    [
+        ("franka.yml", False, 1.0, 500.0),
+        ("franka.yml", True, 0.1, 500.0),
+        ("franka.yml", True, 1.0, 500.0),
+        ("ur5e.yml", False, 1.0, 500.0),
+        ("ur5e.yml", True, 0.1, 500.0),
+        ("ur5e.yml", True, 1.0, 500.0),
+    ],
+)
+def test_motion_gen_trajectory(robot_file, evaluate_interpolated_traj, max_acc, max_jerk):
+    result = run_motion_gen(robot_file, evaluate_interpolated_traj, max_acc, max_jerk)
+
+    assert result.success.item()
+    assert torch.max(torch.abs(result.optimized_plan.acceleration)) <= max_acc
+    assert torch.max(torch.abs(result.optimized_plan.jerk)) <= max_jerk